SatoruDano commited on
Commit
7ae58fa
1 Parent(s): 4f077c3

Upload folder using huggingface_hub

Browse files
README.md CHANGED
@@ -1,3 +1,55 @@
1
  ---
2
- license: llama2
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ base_model: NousResearch/Llama-2-13b-hf
3
+ tags:
4
+ - generated_from_trainer
5
+ model-index:
6
+ - name: lora-out
7
+ results: []
8
  ---
9
+
10
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
+ should probably proofread and complete it, then remove this comment. -->
12
+
13
+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
14
+ # lora-out
15
+
16
+ This model is a fine-tuned version of [NousResearch/Llama-2-13b-hf](https://huggingface.co/NousResearch/Llama-2-13b-hf) on the None dataset.
17
+
18
+ ## Model description
19
+
20
+ More information needed
21
+
22
+ ## Intended uses & limitations
23
+
24
+ More information needed
25
+
26
+ ## Training and evaluation data
27
+
28
+ More information needed
29
+
30
+ ## Training procedure
31
+
32
+ ### Training hyperparameters
33
+
34
+ The following hyperparameters were used during training:
35
+ - learning_rate: 0.0002
36
+ - train_batch_size: 2
37
+ - eval_batch_size: 2
38
+ - seed: 42
39
+ - gradient_accumulation_steps: 4
40
+ - total_train_batch_size: 8
41
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
42
+ - lr_scheduler_type: cosine
43
+ - lr_scheduler_warmup_steps: 10
44
+ - num_epochs: 3
45
+
46
+ ### Training results
47
+
48
+
49
+
50
+ ### Framework versions
51
+
52
+ - Transformers 4.35.0.dev0
53
+ - Pytorch 2.0.1+cu118
54
+ - Datasets 2.14.5
55
+ - Tokenizers 0.14.1
adapter_config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "NousResearch/Llama-2-13b-hf",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 16,
12
+ "lora_dropout": 0.05,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 32,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "down_proj",
20
+ "k_proj",
21
+ "q_proj",
22
+ "v_proj",
23
+ "o_proj",
24
+ "gate_proj",
25
+ "up_proj"
26
+ ],
27
+ "task_type": "CAUSAL_LM"
28
+ }
adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1c2e846b87cb2e39fdef1b1bda39bf462d2ce70c7600b260cbdb54bfc7fd987b
3
+ size 500897101
added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "</s>": 2,
3
+ "<s>": 1,
4
+ "<unk>": 0
5
+ }
checkpoint-3/README.md ADDED
@@ -0,0 +1,219 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: NousResearch/Llama-2-13b-hf
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Shared by [optional]:** [More Information Needed]
22
+ - **Model type:** [More Information Needed]
23
+ - **Language(s) (NLP):** [More Information Needed]
24
+ - **License:** [More Information Needed]
25
+ - **Finetuned from model [optional]:** [More Information Needed]
26
+
27
+ ### Model Sources [optional]
28
+
29
+ <!-- Provide the basic links for the model. -->
30
+
31
+ - **Repository:** [More Information Needed]
32
+ - **Paper [optional]:** [More Information Needed]
33
+ - **Demo [optional]:** [More Information Needed]
34
+
35
+ ## Uses
36
+
37
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
38
+
39
+ ### Direct Use
40
+
41
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
42
+
43
+ [More Information Needed]
44
+
45
+ ### Downstream Use [optional]
46
+
47
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
48
+
49
+ [More Information Needed]
50
+
51
+ ### Out-of-Scope Use
52
+
53
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
54
+
55
+ [More Information Needed]
56
+
57
+ ## Bias, Risks, and Limitations
58
+
59
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
60
+
61
+ [More Information Needed]
62
+
63
+ ### Recommendations
64
+
65
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
66
+
67
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
68
+
69
+ ## How to Get Started with the Model
70
+
71
+ Use the code below to get started with the model.
72
+
73
+ [More Information Needed]
74
+
75
+ ## Training Details
76
+
77
+ ### Training Data
78
+
79
+ <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
80
+
81
+ [More Information Needed]
82
+
83
+ ### Training Procedure
84
+
85
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
86
+
87
+ #### Preprocessing [optional]
88
+
89
+ [More Information Needed]
90
+
91
+
92
+ #### Training Hyperparameters
93
+
94
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
95
+
96
+ #### Speeds, Sizes, Times [optional]
97
+
98
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
99
+
100
+ [More Information Needed]
101
+
102
+ ## Evaluation
103
+
104
+ <!-- This section describes the evaluation protocols and provides the results. -->
105
+
106
+ ### Testing Data, Factors & Metrics
107
+
108
+ #### Testing Data
109
+
110
+ <!-- This should link to a Data Card if possible. -->
111
+
112
+ [More Information Needed]
113
+
114
+ #### Factors
115
+
116
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
117
+
118
+ [More Information Needed]
119
+
120
+ #### Metrics
121
+
122
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
123
+
124
+ [More Information Needed]
125
+
126
+ ### Results
127
+
128
+ [More Information Needed]
129
+
130
+ #### Summary
131
+
132
+
133
+
134
+ ## Model Examination [optional]
135
+
136
+ <!-- Relevant interpretability work for the model goes here -->
137
+
138
+ [More Information Needed]
139
+
140
+ ## Environmental Impact
141
+
142
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
143
+
144
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
145
+
146
+ - **Hardware Type:** [More Information Needed]
147
+ - **Hours used:** [More Information Needed]
148
+ - **Cloud Provider:** [More Information Needed]
149
+ - **Compute Region:** [More Information Needed]
150
+ - **Carbon Emitted:** [More Information Needed]
151
+
152
+ ## Technical Specifications [optional]
153
+
154
+ ### Model Architecture and Objective
155
+
156
+ [More Information Needed]
157
+
158
+ ### Compute Infrastructure
159
+
160
+ [More Information Needed]
161
+
162
+ #### Hardware
163
+
164
+ [More Information Needed]
165
+
166
+ #### Software
167
+
168
+ [More Information Needed]
169
+
170
+ ## Citation [optional]
171
+
172
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
173
+
174
+ **BibTeX:**
175
+
176
+ [More Information Needed]
177
+
178
+ **APA:**
179
+
180
+ [More Information Needed]
181
+
182
+ ## Glossary [optional]
183
+
184
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
185
+
186
+ [More Information Needed]
187
+
188
+ ## More Information [optional]
189
+
190
+ [More Information Needed]
191
+
192
+ ## Model Card Authors [optional]
193
+
194
+ [More Information Needed]
195
+
196
+ ## Model Card Contact
197
+
198
+ [More Information Needed]
199
+
200
+
201
+ ## Training procedure
202
+
203
+
204
+ The following `bitsandbytes` quantization config was used during training:
205
+ - quant_method: bitsandbytes
206
+ - load_in_8bit: True
207
+ - load_in_4bit: False
208
+ - llm_int8_threshold: 6.0
209
+ - llm_int8_skip_modules: None
210
+ - llm_int8_enable_fp32_cpu_offload: False
211
+ - llm_int8_has_fp16_weight: False
212
+ - bnb_4bit_quant_type: fp4
213
+ - bnb_4bit_use_double_quant: False
214
+ - bnb_4bit_compute_dtype: float32
215
+
216
+ ### Framework versions
217
+
218
+
219
+ - PEFT 0.6.0.dev0
checkpoint-3/adapter_config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "NousResearch/Llama-2-13b-hf",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 16,
12
+ "lora_dropout": 0.05,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 32,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "down_proj",
20
+ "k_proj",
21
+ "q_proj",
22
+ "v_proj",
23
+ "o_proj",
24
+ "gate_proj",
25
+ "up_proj"
26
+ ],
27
+ "task_type": "CAUSAL_LM"
28
+ }
checkpoint-3/adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a1416bfcb3510a647c4ce03a1433a71225ba33326dabbfa268e0f0d10e9cf214
3
+ size 500897101
checkpoint-3/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:304e3fd8dd0816342fca8a27e87a8b8446a4e088fa9949c26594313899393cd1
3
+ size 1001736445
checkpoint-3/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fb60e04b9d38bfe8eb07cda80e4ad31525b8dc1994dfa20d160866d959451b8a
3
+ size 14575
checkpoint-3/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5b244e10cd33a7bf97e816a1825baa48fb1ab16018cb603e0581c87980e5f844
3
+ size 627
checkpoint-3/trainer_state.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.0,
5
+ "eval_steps": 20,
6
+ "global_step": 3,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.33,
13
+ "learning_rate": 2e-05,
14
+ "loss": 2.1084,
15
+ "step": 1
16
+ },
17
+ {
18
+ "epoch": 0.67,
19
+ "learning_rate": 4e-05,
20
+ "loss": 2.2032,
21
+ "step": 2
22
+ },
23
+ {
24
+ "epoch": 1.0,
25
+ "learning_rate": 6e-05,
26
+ "loss": 2.1944,
27
+ "step": 3
28
+ }
29
+ ],
30
+ "logging_steps": 1,
31
+ "max_steps": 9,
32
+ "num_train_epochs": 3,
33
+ "save_steps": 500,
34
+ "total_flos": 7654262880337920.0,
35
+ "trial_name": null,
36
+ "trial_params": null
37
+ }
checkpoint-3/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca4b1e140ad4eb932b31f1470fa70dd8e7bb0d5dbc1e2a4704448d45dae9814b
3
+ size 4475
checkpoint-6/README.md ADDED
@@ -0,0 +1,219 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: NousResearch/Llama-2-13b-hf
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Shared by [optional]:** [More Information Needed]
22
+ - **Model type:** [More Information Needed]
23
+ - **Language(s) (NLP):** [More Information Needed]
24
+ - **License:** [More Information Needed]
25
+ - **Finetuned from model [optional]:** [More Information Needed]
26
+
27
+ ### Model Sources [optional]
28
+
29
+ <!-- Provide the basic links for the model. -->
30
+
31
+ - **Repository:** [More Information Needed]
32
+ - **Paper [optional]:** [More Information Needed]
33
+ - **Demo [optional]:** [More Information Needed]
34
+
35
+ ## Uses
36
+
37
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
38
+
39
+ ### Direct Use
40
+
41
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
42
+
43
+ [More Information Needed]
44
+
45
+ ### Downstream Use [optional]
46
+
47
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
48
+
49
+ [More Information Needed]
50
+
51
+ ### Out-of-Scope Use
52
+
53
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
54
+
55
+ [More Information Needed]
56
+
57
+ ## Bias, Risks, and Limitations
58
+
59
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
60
+
61
+ [More Information Needed]
62
+
63
+ ### Recommendations
64
+
65
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
66
+
67
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
68
+
69
+ ## How to Get Started with the Model
70
+
71
+ Use the code below to get started with the model.
72
+
73
+ [More Information Needed]
74
+
75
+ ## Training Details
76
+
77
+ ### Training Data
78
+
79
+ <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
80
+
81
+ [More Information Needed]
82
+
83
+ ### Training Procedure
84
+
85
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
86
+
87
+ #### Preprocessing [optional]
88
+
89
+ [More Information Needed]
90
+
91
+
92
+ #### Training Hyperparameters
93
+
94
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
95
+
96
+ #### Speeds, Sizes, Times [optional]
97
+
98
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
99
+
100
+ [More Information Needed]
101
+
102
+ ## Evaluation
103
+
104
+ <!-- This section describes the evaluation protocols and provides the results. -->
105
+
106
+ ### Testing Data, Factors & Metrics
107
+
108
+ #### Testing Data
109
+
110
+ <!-- This should link to a Data Card if possible. -->
111
+
112
+ [More Information Needed]
113
+
114
+ #### Factors
115
+
116
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
117
+
118
+ [More Information Needed]
119
+
120
+ #### Metrics
121
+
122
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
123
+
124
+ [More Information Needed]
125
+
126
+ ### Results
127
+
128
+ [More Information Needed]
129
+
130
+ #### Summary
131
+
132
+
133
+
134
+ ## Model Examination [optional]
135
+
136
+ <!-- Relevant interpretability work for the model goes here -->
137
+
138
+ [More Information Needed]
139
+
140
+ ## Environmental Impact
141
+
142
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
143
+
144
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
145
+
146
+ - **Hardware Type:** [More Information Needed]
147
+ - **Hours used:** [More Information Needed]
148
+ - **Cloud Provider:** [More Information Needed]
149
+ - **Compute Region:** [More Information Needed]
150
+ - **Carbon Emitted:** [More Information Needed]
151
+
152
+ ## Technical Specifications [optional]
153
+
154
+ ### Model Architecture and Objective
155
+
156
+ [More Information Needed]
157
+
158
+ ### Compute Infrastructure
159
+
160
+ [More Information Needed]
161
+
162
+ #### Hardware
163
+
164
+ [More Information Needed]
165
+
166
+ #### Software
167
+
168
+ [More Information Needed]
169
+
170
+ ## Citation [optional]
171
+
172
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
173
+
174
+ **BibTeX:**
175
+
176
+ [More Information Needed]
177
+
178
+ **APA:**
179
+
180
+ [More Information Needed]
181
+
182
+ ## Glossary [optional]
183
+
184
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
185
+
186
+ [More Information Needed]
187
+
188
+ ## More Information [optional]
189
+
190
+ [More Information Needed]
191
+
192
+ ## Model Card Authors [optional]
193
+
194
+ [More Information Needed]
195
+
196
+ ## Model Card Contact
197
+
198
+ [More Information Needed]
199
+
200
+
201
+ ## Training procedure
202
+
203
+
204
+ The following `bitsandbytes` quantization config was used during training:
205
+ - quant_method: bitsandbytes
206
+ - load_in_8bit: True
207
+ - load_in_4bit: False
208
+ - llm_int8_threshold: 6.0
209
+ - llm_int8_skip_modules: None
210
+ - llm_int8_enable_fp32_cpu_offload: False
211
+ - llm_int8_has_fp16_weight: False
212
+ - bnb_4bit_quant_type: fp4
213
+ - bnb_4bit_use_double_quant: False
214
+ - bnb_4bit_compute_dtype: float32
215
+
216
+ ### Framework versions
217
+
218
+
219
+ - PEFT 0.6.0.dev0
checkpoint-6/adapter_config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "NousResearch/Llama-2-13b-hf",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 16,
12
+ "lora_dropout": 0.05,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 32,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "down_proj",
20
+ "k_proj",
21
+ "q_proj",
22
+ "v_proj",
23
+ "o_proj",
24
+ "gate_proj",
25
+ "up_proj"
26
+ ],
27
+ "task_type": "CAUSAL_LM"
28
+ }
checkpoint-6/adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:12c86a12eb1af311c45aa1834e1c76a3491e91589463dfbed73678132e638f30
3
+ size 500897101
checkpoint-6/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5ef7aac1705e5c9dbf87ae1baee0ca91cd2dec685ffc29821a10215594a81ce9
3
+ size 1001736445
checkpoint-6/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3c354cd6e9f3ddb9e3138339580e36bdec4a0dbc932a20f927ad306080f662c6
3
+ size 14575
checkpoint-6/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f366261eb5f87adcfef3dae0b55753e6918a14c8fed0139c6ca4cdb9f6d8d084
3
+ size 627
checkpoint-6/trainer_state.json ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.0,
5
+ "eval_steps": 20,
6
+ "global_step": 6,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.33,
13
+ "learning_rate": 2e-05,
14
+ "loss": 2.1084,
15
+ "step": 1
16
+ },
17
+ {
18
+ "epoch": 0.67,
19
+ "learning_rate": 4e-05,
20
+ "loss": 2.2032,
21
+ "step": 2
22
+ },
23
+ {
24
+ "epoch": 1.0,
25
+ "learning_rate": 6e-05,
26
+ "loss": 2.1944,
27
+ "step": 3
28
+ },
29
+ {
30
+ "epoch": 1.33,
31
+ "learning_rate": 8e-05,
32
+ "loss": 2.166,
33
+ "step": 4
34
+ },
35
+ {
36
+ "epoch": 1.67,
37
+ "learning_rate": 0.0001,
38
+ "loss": 2.1799,
39
+ "step": 5
40
+ },
41
+ {
42
+ "epoch": 2.0,
43
+ "learning_rate": 0.00012,
44
+ "loss": 2.1193,
45
+ "step": 6
46
+ }
47
+ ],
48
+ "logging_steps": 1,
49
+ "max_steps": 9,
50
+ "num_train_epochs": 3,
51
+ "save_steps": 500,
52
+ "total_flos": 1.530852576067584e+16,
53
+ "trial_name": null,
54
+ "trial_params": null
55
+ }
checkpoint-6/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca4b1e140ad4eb932b31f1470fa70dd8e7bb0d5dbc1e2a4704448d45dae9814b
3
+ size 4475
checkpoint-9/README.md ADDED
@@ -0,0 +1,219 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: NousResearch/Llama-2-13b-hf
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Shared by [optional]:** [More Information Needed]
22
+ - **Model type:** [More Information Needed]
23
+ - **Language(s) (NLP):** [More Information Needed]
24
+ - **License:** [More Information Needed]
25
+ - **Finetuned from model [optional]:** [More Information Needed]
26
+
27
+ ### Model Sources [optional]
28
+
29
+ <!-- Provide the basic links for the model. -->
30
+
31
+ - **Repository:** [More Information Needed]
32
+ - **Paper [optional]:** [More Information Needed]
33
+ - **Demo [optional]:** [More Information Needed]
34
+
35
+ ## Uses
36
+
37
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
38
+
39
+ ### Direct Use
40
+
41
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
42
+
43
+ [More Information Needed]
44
+
45
+ ### Downstream Use [optional]
46
+
47
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
48
+
49
+ [More Information Needed]
50
+
51
+ ### Out-of-Scope Use
52
+
53
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
54
+
55
+ [More Information Needed]
56
+
57
+ ## Bias, Risks, and Limitations
58
+
59
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
60
+
61
+ [More Information Needed]
62
+
63
+ ### Recommendations
64
+
65
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
66
+
67
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
68
+
69
+ ## How to Get Started with the Model
70
+
71
+ Use the code below to get started with the model.
72
+
73
+ [More Information Needed]
74
+
75
+ ## Training Details
76
+
77
+ ### Training Data
78
+
79
+ <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
80
+
81
+ [More Information Needed]
82
+
83
+ ### Training Procedure
84
+
85
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
86
+
87
+ #### Preprocessing [optional]
88
+
89
+ [More Information Needed]
90
+
91
+
92
+ #### Training Hyperparameters
93
+
94
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
95
+
96
+ #### Speeds, Sizes, Times [optional]
97
+
98
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
99
+
100
+ [More Information Needed]
101
+
102
+ ## Evaluation
103
+
104
+ <!-- This section describes the evaluation protocols and provides the results. -->
105
+
106
+ ### Testing Data, Factors & Metrics
107
+
108
+ #### Testing Data
109
+
110
+ <!-- This should link to a Data Card if possible. -->
111
+
112
+ [More Information Needed]
113
+
114
+ #### Factors
115
+
116
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
117
+
118
+ [More Information Needed]
119
+
120
+ #### Metrics
121
+
122
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
123
+
124
+ [More Information Needed]
125
+
126
+ ### Results
127
+
128
+ [More Information Needed]
129
+
130
+ #### Summary
131
+
132
+
133
+
134
+ ## Model Examination [optional]
135
+
136
+ <!-- Relevant interpretability work for the model goes here -->
137
+
138
+ [More Information Needed]
139
+
140
+ ## Environmental Impact
141
+
142
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
143
+
144
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
145
+
146
+ - **Hardware Type:** [More Information Needed]
147
+ - **Hours used:** [More Information Needed]
148
+ - **Cloud Provider:** [More Information Needed]
149
+ - **Compute Region:** [More Information Needed]
150
+ - **Carbon Emitted:** [More Information Needed]
151
+
152
+ ## Technical Specifications [optional]
153
+
154
+ ### Model Architecture and Objective
155
+
156
+ [More Information Needed]
157
+
158
+ ### Compute Infrastructure
159
+
160
+ [More Information Needed]
161
+
162
+ #### Hardware
163
+
164
+ [More Information Needed]
165
+
166
+ #### Software
167
+
168
+ [More Information Needed]
169
+
170
+ ## Citation [optional]
171
+
172
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
173
+
174
+ **BibTeX:**
175
+
176
+ [More Information Needed]
177
+
178
+ **APA:**
179
+
180
+ [More Information Needed]
181
+
182
+ ## Glossary [optional]
183
+
184
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
185
+
186
+ [More Information Needed]
187
+
188
+ ## More Information [optional]
189
+
190
+ [More Information Needed]
191
+
192
+ ## Model Card Authors [optional]
193
+
194
+ [More Information Needed]
195
+
196
+ ## Model Card Contact
197
+
198
+ [More Information Needed]
199
+
200
+
201
+ ## Training procedure
202
+
203
+
204
+ The following `bitsandbytes` quantization config was used during training:
205
+ - quant_method: bitsandbytes
206
+ - load_in_8bit: True
207
+ - load_in_4bit: False
208
+ - llm_int8_threshold: 6.0
209
+ - llm_int8_skip_modules: None
210
+ - llm_int8_enable_fp32_cpu_offload: False
211
+ - llm_int8_has_fp16_weight: False
212
+ - bnb_4bit_quant_type: fp4
213
+ - bnb_4bit_use_double_quant: False
214
+ - bnb_4bit_compute_dtype: float32
215
+
216
+ ### Framework versions
217
+
218
+
219
+ - PEFT 0.6.0.dev0
checkpoint-9/adapter_config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "NousResearch/Llama-2-13b-hf",
5
+ "bias": "none",
6
+ "fan_in_fan_out": null,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layers_pattern": null,
10
+ "layers_to_transform": null,
11
+ "lora_alpha": 16,
12
+ "lora_dropout": 0.05,
13
+ "modules_to_save": null,
14
+ "peft_type": "LORA",
15
+ "r": 32,
16
+ "rank_pattern": {},
17
+ "revision": null,
18
+ "target_modules": [
19
+ "down_proj",
20
+ "k_proj",
21
+ "q_proj",
22
+ "v_proj",
23
+ "o_proj",
24
+ "gate_proj",
25
+ "up_proj"
26
+ ],
27
+ "task_type": "CAUSAL_LM"
28
+ }
checkpoint-9/adapter_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1c2e846b87cb2e39fdef1b1bda39bf462d2ce70c7600b260cbdb54bfc7fd987b
3
+ size 500897101
checkpoint-9/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b7ad102eea08f06c24480d8d00332428c6f7df93ecbaca59e17e0621d83f2854
3
+ size 1001736445
checkpoint-9/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dea21e80930da893f12ad529906ad07a7595e8e8bc42aa059c7bd25f8ec58237
3
+ size 14575
checkpoint-9/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:82bff8c9f183a04cf2183a5529627973f5e36add2462582651217f5da45d4c95
3
+ size 627
checkpoint-9/trainer_state.json ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 3.0,
5
+ "eval_steps": 20,
6
+ "global_step": 9,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.33,
13
+ "learning_rate": 2e-05,
14
+ "loss": 2.1084,
15
+ "step": 1
16
+ },
17
+ {
18
+ "epoch": 0.67,
19
+ "learning_rate": 4e-05,
20
+ "loss": 2.2032,
21
+ "step": 2
22
+ },
23
+ {
24
+ "epoch": 1.0,
25
+ "learning_rate": 6e-05,
26
+ "loss": 2.1944,
27
+ "step": 3
28
+ },
29
+ {
30
+ "epoch": 1.33,
31
+ "learning_rate": 8e-05,
32
+ "loss": 2.166,
33
+ "step": 4
34
+ },
35
+ {
36
+ "epoch": 1.67,
37
+ "learning_rate": 0.0001,
38
+ "loss": 2.1799,
39
+ "step": 5
40
+ },
41
+ {
42
+ "epoch": 2.0,
43
+ "learning_rate": 0.00012,
44
+ "loss": 2.1193,
45
+ "step": 6
46
+ },
47
+ {
48
+ "epoch": 2.33,
49
+ "learning_rate": 0.00014,
50
+ "loss": 2.1065,
51
+ "step": 7
52
+ },
53
+ {
54
+ "epoch": 2.67,
55
+ "learning_rate": 0.00016,
56
+ "loss": 1.9974,
57
+ "step": 8
58
+ },
59
+ {
60
+ "epoch": 3.0,
61
+ "learning_rate": 0.00018,
62
+ "loss": 1.8511,
63
+ "step": 9
64
+ }
65
+ ],
66
+ "logging_steps": 1,
67
+ "max_steps": 9,
68
+ "num_train_epochs": 3,
69
+ "save_steps": 500,
70
+ "total_flos": 2.296278864101376e+16,
71
+ "trial_name": null,
72
+ "trial_params": null
73
+ }
checkpoint-9/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca4b1e140ad4eb932b31f1470fa70dd8e7bb0d5dbc1e2a4704448d45dae9814b
3
+ size 4475
config.json ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "NousResearch/Llama-2-13b-hf",
3
+ "architectures": [
4
+ "LlamaForCausalLM"
5
+ ],
6
+ "attention_bias": false,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 5120,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 13824,
13
+ "max_position_embeddings": 4096,
14
+ "model_type": "llama",
15
+ "num_attention_heads": 40,
16
+ "num_hidden_layers": 40,
17
+ "num_key_value_heads": 40,
18
+ "pad_token_id": 0,
19
+ "pretraining_tp": 1,
20
+ "quantization_config": {
21
+ "bnb_4bit_compute_dtype": "float32",
22
+ "bnb_4bit_quant_type": "fp4",
23
+ "bnb_4bit_use_double_quant": false,
24
+ "llm_int8_enable_fp32_cpu_offload": false,
25
+ "llm_int8_has_fp16_weight": false,
26
+ "llm_int8_skip_modules": null,
27
+ "llm_int8_threshold": 6.0,
28
+ "load_in_4bit": false,
29
+ "load_in_8bit": true,
30
+ "quant_method": "bitsandbytes"
31
+ },
32
+ "rms_norm_eps": 1e-05,
33
+ "rope_scaling": null,
34
+ "rope_theta": 10000.0,
35
+ "tie_word_embeddings": false,
36
+ "torch_dtype": "float16",
37
+ "transformers_version": "4.35.0.dev0",
38
+ "use_cache": false,
39
+ "vocab_size": 32000
40
+ }
merged/added_tokens.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "</s>": 2,
3
+ "<s>": 1,
4
+ "<unk>": 0
5
+ }
merged/config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "NousResearch/Llama-2-13b-hf",
3
+ "architectures": [
4
+ "LlamaForCausalLM"
5
+ ],
6
+ "attention_bias": false,
7
+ "bos_token_id": 1,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "silu",
10
+ "hidden_size": 5120,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 13824,
13
+ "max_position_embeddings": 4096,
14
+ "model_type": "llama",
15
+ "num_attention_heads": 40,
16
+ "num_hidden_layers": 40,
17
+ "num_key_value_heads": 40,
18
+ "pad_token_id": 0,
19
+ "pretraining_tp": 1,
20
+ "rms_norm_eps": 1e-05,
21
+ "rope_scaling": null,
22
+ "rope_theta": 10000.0,
23
+ "tie_word_embeddings": false,
24
+ "torch_dtype": "float16",
25
+ "transformers_version": "4.35.0.dev0",
26
+ "use_cache": false,
27
+ "vocab_size": 32000
28
+ }
merged/pytorch_model-00001-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a89465b511f73df4ad6091ece58cf224352dad09581563bb743a962ccc7faa84
3
+ size 9948721353
merged/pytorch_model-00002-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1d0631a6226cf8c899c1c0ff55424ac168e89f2702ac1a3c53a922fcafc84ba1
3
+ size 9904157328
merged/pytorch_model-00003-of-00003.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3a424c651ae8f1283acfc40453478be97265af5b53cdf14a1e48fa07241658d
3
+ size 6178979423
merged/pytorch_model.bin.index.json ADDED
@@ -0,0 +1,370 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "total_size": 26031728640
4
+ },
5
+ "weight_map": {
6
+ "lm_head.weight": "pytorch_model-00003-of-00003.bin",
7
+ "model.embed_tokens.weight": "pytorch_model-00001-of-00003.bin",
8
+ "model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
9
+ "model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
10
+ "model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
11
+ "model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
12
+ "model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
13
+ "model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
14
+ "model.layers.0.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
15
+ "model.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
16
+ "model.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
17
+ "model.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
18
+ "model.layers.1.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
19
+ "model.layers.1.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
20
+ "model.layers.1.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
21
+ "model.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
22
+ "model.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
23
+ "model.layers.1.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
24
+ "model.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
25
+ "model.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
26
+ "model.layers.10.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
27
+ "model.layers.10.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
28
+ "model.layers.10.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
29
+ "model.layers.10.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
30
+ "model.layers.10.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
31
+ "model.layers.10.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
32
+ "model.layers.10.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
33
+ "model.layers.10.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
34
+ "model.layers.10.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
35
+ "model.layers.11.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
36
+ "model.layers.11.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
37
+ "model.layers.11.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
38
+ "model.layers.11.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
39
+ "model.layers.11.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
40
+ "model.layers.11.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
41
+ "model.layers.11.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
42
+ "model.layers.11.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
43
+ "model.layers.11.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
44
+ "model.layers.12.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
45
+ "model.layers.12.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
46
+ "model.layers.12.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
47
+ "model.layers.12.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
48
+ "model.layers.12.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
49
+ "model.layers.12.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
50
+ "model.layers.12.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
51
+ "model.layers.12.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
52
+ "model.layers.12.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
53
+ "model.layers.13.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
54
+ "model.layers.13.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
55
+ "model.layers.13.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
56
+ "model.layers.13.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
57
+ "model.layers.13.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
58
+ "model.layers.13.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
59
+ "model.layers.13.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
60
+ "model.layers.13.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
61
+ "model.layers.13.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
62
+ "model.layers.14.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
63
+ "model.layers.14.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
64
+ "model.layers.14.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
65
+ "model.layers.14.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
66
+ "model.layers.14.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
67
+ "model.layers.14.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
68
+ "model.layers.14.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
69
+ "model.layers.14.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
70
+ "model.layers.14.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
71
+ "model.layers.15.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
72
+ "model.layers.15.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
73
+ "model.layers.15.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
74
+ "model.layers.15.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
75
+ "model.layers.15.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
76
+ "model.layers.15.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
77
+ "model.layers.15.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
78
+ "model.layers.15.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
79
+ "model.layers.15.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
80
+ "model.layers.16.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
81
+ "model.layers.16.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
82
+ "model.layers.16.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
83
+ "model.layers.16.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
84
+ "model.layers.16.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
85
+ "model.layers.16.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
86
+ "model.layers.16.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
87
+ "model.layers.16.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
88
+ "model.layers.16.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
89
+ "model.layers.17.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
90
+ "model.layers.17.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
91
+ "model.layers.17.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
92
+ "model.layers.17.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
93
+ "model.layers.17.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
94
+ "model.layers.17.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
95
+ "model.layers.17.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
96
+ "model.layers.17.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
97
+ "model.layers.17.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
98
+ "model.layers.18.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
99
+ "model.layers.18.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
100
+ "model.layers.18.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
101
+ "model.layers.18.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
102
+ "model.layers.18.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
103
+ "model.layers.18.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
104
+ "model.layers.18.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
105
+ "model.layers.18.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
106
+ "model.layers.18.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
107
+ "model.layers.19.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
108
+ "model.layers.19.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
109
+ "model.layers.19.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
110
+ "model.layers.19.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
111
+ "model.layers.19.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
112
+ "model.layers.19.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
113
+ "model.layers.19.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
114
+ "model.layers.19.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
115
+ "model.layers.19.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
116
+ "model.layers.2.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
117
+ "model.layers.2.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
118
+ "model.layers.2.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
119
+ "model.layers.2.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
120
+ "model.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
121
+ "model.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
122
+ "model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
123
+ "model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
124
+ "model.layers.2.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
125
+ "model.layers.20.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
126
+ "model.layers.20.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
127
+ "model.layers.20.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
128
+ "model.layers.20.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
129
+ "model.layers.20.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
130
+ "model.layers.20.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
131
+ "model.layers.20.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
132
+ "model.layers.20.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
133
+ "model.layers.20.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
134
+ "model.layers.21.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
135
+ "model.layers.21.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
136
+ "model.layers.21.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
137
+ "model.layers.21.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
138
+ "model.layers.21.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
139
+ "model.layers.21.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
140
+ "model.layers.21.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
141
+ "model.layers.21.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
142
+ "model.layers.21.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
143
+ "model.layers.22.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
144
+ "model.layers.22.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
145
+ "model.layers.22.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
146
+ "model.layers.22.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
147
+ "model.layers.22.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
148
+ "model.layers.22.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
149
+ "model.layers.22.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
150
+ "model.layers.22.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
151
+ "model.layers.22.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
152
+ "model.layers.23.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
153
+ "model.layers.23.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
154
+ "model.layers.23.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
155
+ "model.layers.23.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
156
+ "model.layers.23.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
157
+ "model.layers.23.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
158
+ "model.layers.23.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
159
+ "model.layers.23.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
160
+ "model.layers.23.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
161
+ "model.layers.24.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
162
+ "model.layers.24.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
163
+ "model.layers.24.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
164
+ "model.layers.24.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
165
+ "model.layers.24.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
166
+ "model.layers.24.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
167
+ "model.layers.24.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
168
+ "model.layers.24.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
169
+ "model.layers.24.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
170
+ "model.layers.25.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
171
+ "model.layers.25.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
172
+ "model.layers.25.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
173
+ "model.layers.25.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
174
+ "model.layers.25.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
175
+ "model.layers.25.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
176
+ "model.layers.25.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
177
+ "model.layers.25.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
178
+ "model.layers.25.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
179
+ "model.layers.26.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
180
+ "model.layers.26.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
181
+ "model.layers.26.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
182
+ "model.layers.26.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
183
+ "model.layers.26.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
184
+ "model.layers.26.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
185
+ "model.layers.26.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
186
+ "model.layers.26.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
187
+ "model.layers.26.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
188
+ "model.layers.27.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
189
+ "model.layers.27.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
190
+ "model.layers.27.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
191
+ "model.layers.27.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
192
+ "model.layers.27.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
193
+ "model.layers.27.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
194
+ "model.layers.27.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
195
+ "model.layers.27.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
196
+ "model.layers.27.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
197
+ "model.layers.28.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
198
+ "model.layers.28.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
199
+ "model.layers.28.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
200
+ "model.layers.28.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
201
+ "model.layers.28.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
202
+ "model.layers.28.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
203
+ "model.layers.28.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
204
+ "model.layers.28.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
205
+ "model.layers.28.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
206
+ "model.layers.29.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
207
+ "model.layers.29.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin",
208
+ "model.layers.29.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
209
+ "model.layers.29.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
210
+ "model.layers.29.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
211
+ "model.layers.29.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
212
+ "model.layers.29.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
213
+ "model.layers.29.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
214
+ "model.layers.29.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
215
+ "model.layers.3.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
216
+ "model.layers.3.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
217
+ "model.layers.3.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
218
+ "model.layers.3.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
219
+ "model.layers.3.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
220
+ "model.layers.3.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
221
+ "model.layers.3.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
222
+ "model.layers.3.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
223
+ "model.layers.3.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
224
+ "model.layers.30.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
225
+ "model.layers.30.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
226
+ "model.layers.30.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin",
227
+ "model.layers.30.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin",
228
+ "model.layers.30.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
229
+ "model.layers.30.self_attn.k_proj.weight": "pytorch_model-00002-of-00003.bin",
230
+ "model.layers.30.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin",
231
+ "model.layers.30.self_attn.q_proj.weight": "pytorch_model-00002-of-00003.bin",
232
+ "model.layers.30.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin",
233
+ "model.layers.31.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
234
+ "model.layers.31.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
235
+ "model.layers.31.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
236
+ "model.layers.31.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
237
+ "model.layers.31.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
238
+ "model.layers.31.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
239
+ "model.layers.31.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
240
+ "model.layers.31.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
241
+ "model.layers.31.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
242
+ "model.layers.32.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
243
+ "model.layers.32.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
244
+ "model.layers.32.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
245
+ "model.layers.32.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
246
+ "model.layers.32.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
247
+ "model.layers.32.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
248
+ "model.layers.32.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
249
+ "model.layers.32.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
250
+ "model.layers.32.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
251
+ "model.layers.33.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
252
+ "model.layers.33.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
253
+ "model.layers.33.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
254
+ "model.layers.33.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
255
+ "model.layers.33.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
256
+ "model.layers.33.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
257
+ "model.layers.33.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
258
+ "model.layers.33.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
259
+ "model.layers.33.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
260
+ "model.layers.34.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
261
+ "model.layers.34.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
262
+ "model.layers.34.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
263
+ "model.layers.34.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
264
+ "model.layers.34.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
265
+ "model.layers.34.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
266
+ "model.layers.34.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
267
+ "model.layers.34.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
268
+ "model.layers.34.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
269
+ "model.layers.35.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
270
+ "model.layers.35.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
271
+ "model.layers.35.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
272
+ "model.layers.35.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
273
+ "model.layers.35.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
274
+ "model.layers.35.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
275
+ "model.layers.35.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
276
+ "model.layers.35.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
277
+ "model.layers.35.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
278
+ "model.layers.36.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
279
+ "model.layers.36.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
280
+ "model.layers.36.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
281
+ "model.layers.36.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
282
+ "model.layers.36.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
283
+ "model.layers.36.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
284
+ "model.layers.36.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
285
+ "model.layers.36.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
286
+ "model.layers.36.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
287
+ "model.layers.37.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
288
+ "model.layers.37.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
289
+ "model.layers.37.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
290
+ "model.layers.37.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
291
+ "model.layers.37.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
292
+ "model.layers.37.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
293
+ "model.layers.37.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
294
+ "model.layers.37.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
295
+ "model.layers.37.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
296
+ "model.layers.38.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
297
+ "model.layers.38.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
298
+ "model.layers.38.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
299
+ "model.layers.38.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
300
+ "model.layers.38.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
301
+ "model.layers.38.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
302
+ "model.layers.38.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
303
+ "model.layers.38.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
304
+ "model.layers.38.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
305
+ "model.layers.39.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
306
+ "model.layers.39.mlp.down_proj.weight": "pytorch_model-00003-of-00003.bin",
307
+ "model.layers.39.mlp.gate_proj.weight": "pytorch_model-00003-of-00003.bin",
308
+ "model.layers.39.mlp.up_proj.weight": "pytorch_model-00003-of-00003.bin",
309
+ "model.layers.39.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
310
+ "model.layers.39.self_attn.k_proj.weight": "pytorch_model-00003-of-00003.bin",
311
+ "model.layers.39.self_attn.o_proj.weight": "pytorch_model-00003-of-00003.bin",
312
+ "model.layers.39.self_attn.q_proj.weight": "pytorch_model-00003-of-00003.bin",
313
+ "model.layers.39.self_attn.v_proj.weight": "pytorch_model-00003-of-00003.bin",
314
+ "model.layers.4.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
315
+ "model.layers.4.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
316
+ "model.layers.4.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
317
+ "model.layers.4.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
318
+ "model.layers.4.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
319
+ "model.layers.4.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
320
+ "model.layers.4.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
321
+ "model.layers.4.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
322
+ "model.layers.4.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
323
+ "model.layers.5.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
324
+ "model.layers.5.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
325
+ "model.layers.5.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
326
+ "model.layers.5.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
327
+ "model.layers.5.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
328
+ "model.layers.5.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
329
+ "model.layers.5.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
330
+ "model.layers.5.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
331
+ "model.layers.5.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
332
+ "model.layers.6.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
333
+ "model.layers.6.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
334
+ "model.layers.6.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
335
+ "model.layers.6.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
336
+ "model.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
337
+ "model.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
338
+ "model.layers.6.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
339
+ "model.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
340
+ "model.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
341
+ "model.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
342
+ "model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
343
+ "model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
344
+ "model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
345
+ "model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
346
+ "model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
347
+ "model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
348
+ "model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
349
+ "model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
350
+ "model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
351
+ "model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
352
+ "model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
353
+ "model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
354
+ "model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
355
+ "model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
356
+ "model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
357
+ "model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
358
+ "model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
359
+ "model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
360
+ "model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
361
+ "model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
362
+ "model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
363
+ "model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
364
+ "model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
365
+ "model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
366
+ "model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
367
+ "model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
368
+ "model.norm.weight": "pytorch_model-00003-of-00003.bin"
369
+ }
370
+ }
merged/special_tokens_map.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": "<s>",
3
+ "eos_token": "</s>",
4
+ "pad_token": "<unk>",
5
+ "unk_token": "<unk>"
6
+ }
merged/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
merged/tokenizer_config.json ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [],
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "legacy": false,
35
+ "model_max_length": 1000000000000000019884624838656,
36
+ "pad_token": "<unk>",
37
+ "sp_model_kwargs": {},
38
+ "spaces_between_special_tokens": false,
39
+ "tokenizer_class": "LlamaTokenizer",
40
+ "tokenizer_file": null,
41
+ "trust_remote_code": false,
42
+ "unk_token": "<unk>",
43
+ "use_default_system_prompt": true,
44
+ "use_fast": true
45
+ }
runs/Oct12_19-18-08_0c6efc15e76d/events.out.tfevents.1697138289.0c6efc15e76d.7390.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:224ac31c7391b1882286cb7c10a5543779d017d94caea19b912465a253165c9e
3
+ size 6695
special_tokens_map.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": "<s>",
3
+ "eos_token": "</s>",
4
+ "pad_token": "<unk>",
5
+ "unk_token": "<unk>"
6
+ }
tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
3
+ size 499723
tokenizer_config.json ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<unk>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<s>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "</s>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ }
29
+ },
30
+ "additional_special_tokens": [],
31
+ "bos_token": "<s>",
32
+ "clean_up_tokenization_spaces": false,
33
+ "eos_token": "</s>",
34
+ "legacy": false,
35
+ "model_max_length": 1000000000000000019884624838656,
36
+ "pad_token": "<unk>",
37
+ "sp_model_kwargs": {},
38
+ "spaces_between_special_tokens": false,
39
+ "tokenizer_class": "LlamaTokenizer",
40
+ "tokenizer_file": null,
41
+ "trust_remote_code": false,
42
+ "unk_token": "<unk>",
43
+ "use_default_system_prompt": true,
44
+ "use_fast": true
45
+ }