Hugging Face's logo

ryan0712
/
llama-3-8b-slow-DUS-max-layer2-method2

Text Generation
Transformers
Safetensors
llama
Merge
mergekit
lazymergekit
NousResearch/Meta-Llama-3-8B
text-generation-inference
Inference Endpoints
Model card Files Community
llama-3-8b-slow-DUS-max-layer2-method2
File size: 4,613 Bytes 
51b37f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
 
---
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Meta-Llama-3-8B
base_model:
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
- NousResearch/Meta-Llama-3-8B
---

# llama-3-8b-slow-DUS-max-layer2-method2

llama-3-8b-slow-DUS-max-layer2-method2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)
* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B)

## 🧩 Configuration

```yaml
slices:

      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [1, 2]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [2, 3]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [3, 4]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [4, 5]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [5, 6]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [6, 7]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [7, 8]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [8, 9]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [9, 10]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [10, 11]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [11, 12]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [12, 13]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [13, 14]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [14, 15]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [15, 16]
    
      - sources:
          - model: NousResearch/Meta-Llama-3-8B
            layer_range: [31, 32]
    
merge_method: passthrough
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "ryan0712/llama-3-8b-slow-DUS-max-layer2-method2"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```