Upload folder using huggingface_hub (#1)
Browse files- 1c9840a69052cc6f22dbe8e5ac14ba57d55590c1ae84c49a1c5e92a5b70f2a95 (4e4305e7fa8ce60b0dfdc8b6c43f641e17f32e2a)
- af7c1efdf404a65cede76ff2134f6e1d26c797e7512caf647234a474043a4c24 (d19f29031200cab559704e6e37642718b7575cc1)
- README.md +85 -0
- config.json +47 -0
- generation_config.json +6 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +878 -0
- smash_config.json +31 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +215 -0
README.md
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---
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thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
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base_model: EleutherAI/pythia-12b
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metrics:
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- memory_disk
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- memory_inference
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- inference_latency
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- inference_throughput
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- inference_CO2_emissions
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- inference_energy_consumption
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tags:
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- pruna-ai
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---
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<!-- header start -->
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<!-- 200823 -->
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
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<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</a>
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</div>
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<!-- header end -->
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[](https://twitter.com/PrunaAI)
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[](https://github.com/PrunaAI)
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[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
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[](https://discord.gg/CP4VSgck)
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# Simply make AI models cheaper, smaller, faster, and greener!
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- Give a thumbs up if you like this model!
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| 31 |
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
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| 32 |
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- Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
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| 33 |
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- Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
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| 34 |
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- Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
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| 35 |
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## Results
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**Frequently Asked Questions**
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- ***How does the compression work?*** The model is compressed with llm-int8.
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- ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
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- ***How is the model efficiency evaluated?*** These results were obtained on HARDWARE_NAME with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
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- ***What is the model format?*** We use safetensors.
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- ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
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- ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
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| 47 |
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- ***How to compress my own models?*** You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
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| 48 |
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- ***What are "first" metrics?*** Results mentioning "first" are obtained after the first run of the model. The first run might take more memory or be slower than the subsequent runs due cuda overheads.
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- ***What are "Sync" and "Async" metrics?*** "Sync" metrics are obtained by syncing all GPU processes and stop measurement when all of them are executed. "Async" metrics are obtained without syncing all GPU processes and stop when the model output can be used by the CPU. We provide both metrics since both could be relevant depending on the use-case. We recommend to test the efficiency gains directly in your use-cases.
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## Setup
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You can run the smashed model with these steps:
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0. Check requirements from the original repo EleutherAI/pythia-12b installed. In particular, check python, cuda, and transformers versions.
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1. Make sure that you have installed quantization related packages.
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| 57 |
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```bash
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pip install transformers accelerate bitsandbytes>0.37.0
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| 59 |
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```
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2. Load & run the model.
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| 61 |
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```python
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| 62 |
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from transformers import AutoModelForCausalLM, AutoTokenizer
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| 63 |
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model = AutoModelForCausalLM.from_pretrained("PrunaAI/EleutherAI-pythia-12b-bnb-4bit-smashed", trust_remote_code=True, device_map='auto')
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| 66 |
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tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pythia-12b")
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| 67 |
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|
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input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
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outputs = model.generate(input_ids, max_new_tokens=216)
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tokenizer.decode(outputs[0])
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```
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## Configurations
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The configuration info are in `smash_config.json`.
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## Credits & License
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The license of the smashed model follows the license of the original model. Please check the license of the original model EleutherAI/pythia-12b before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi.
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|
| 82 |
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## Want to compress other models?
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| 83 |
+
|
| 84 |
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- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
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| 85 |
+
- Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
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config.json
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{
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"_name_or_path": "/ceph/hdd/staff/charpent/.cache/models0bym86_d_abo5b3s",
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| 3 |
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"architectures": [
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| 4 |
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"GPTNeoXForCausalLM"
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| 5 |
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],
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| 6 |
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"attention_bias": true,
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| 7 |
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"attention_dropout": 0.0,
|
| 8 |
+
"bos_token_id": 0,
|
| 9 |
+
"classifier_dropout": 0.1,
|
| 10 |
+
"eos_token_id": 0,
|
| 11 |
+
"hidden_act": "gelu",
|
| 12 |
+
"hidden_dropout": 0.0,
|
| 13 |
+
"hidden_size": 5120,
|
| 14 |
+
"initializer_range": 0.02,
|
| 15 |
+
"intermediate_size": 20480,
|
| 16 |
+
"layer_norm_eps": 1e-05,
|
| 17 |
+
"max_position_embeddings": 2048,
|
| 18 |
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"model_type": "gpt_neox",
|
| 19 |
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"num_attention_heads": 40,
|
| 20 |
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"num_hidden_layers": 36,
|
| 21 |
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"quantization_config": {
|
| 22 |
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"_load_in_4bit": true,
|
| 23 |
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"_load_in_8bit": false,
|
| 24 |
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"bnb_4bit_compute_dtype": "bfloat16",
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| 25 |
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"bnb_4bit_quant_storage": "uint8",
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| 26 |
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"bnb_4bit_quant_type": "fp4",
|
| 27 |
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"bnb_4bit_use_double_quant": false,
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| 28 |
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"llm_int8_enable_fp32_cpu_offload": false,
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| 29 |
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"llm_int8_has_fp16_weight": false,
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| 30 |
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"llm_int8_skip_modules": [
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| 31 |
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"lm_head"
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| 32 |
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],
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| 33 |
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"llm_int8_threshold": 6.0,
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| 34 |
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"load_in_4bit": true,
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| 35 |
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"load_in_8bit": false,
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| 36 |
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"quant_method": "bitsandbytes"
|
| 37 |
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},
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| 38 |
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"rope_scaling": null,
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| 39 |
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"rotary_emb_base": 10000,
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| 40 |
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"rotary_pct": 0.25,
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| 41 |
+
"tie_word_embeddings": false,
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| 42 |
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"torch_dtype": "float16",
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| 43 |
+
"transformers_version": "4.41.2",
|
| 44 |
+
"use_cache": true,
|
| 45 |
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"use_parallel_residual": true,
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| 46 |
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"vocab_size": 50688
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| 47 |
+
}
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generation_config.json
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{
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| 2 |
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"_from_model_config": true,
|
| 3 |
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"bos_token_id": 0,
|
| 4 |
+
"eos_token_id": 0,
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| 5 |
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"transformers_version": "4.41.2"
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| 6 |
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}
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:b8e5b994c49f394f9b2452bd8b99ad28c7c888008d323f810f1a17a9d5ec369e
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| 3 |
+
size 4990452185
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:304fc17e6f0743344d7e59aa1f6f1fe3cd86bd2306eb012b625275a696cae29e
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| 3 |
+
size 2049615541
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model.safetensors.index.json
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|
| 826 |
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|
| 827 |
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|
| 828 |
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|
| 829 |
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|
| 830 |
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|
| 831 |
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|
| 832 |
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|
| 833 |
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|
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|
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|
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|
| 837 |
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|
| 838 |
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|
| 839 |
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|
| 840 |
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|
| 841 |
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"gpt_neox.layers.8.mlp.dense_4h_to_h.bias": "model-00001-of-00002.safetensors",
|
| 842 |
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|
| 843 |
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|
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|
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|
| 846 |
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|
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|
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|
| 849 |
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| 850 |
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|
| 851 |
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|
| 852 |
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|
| 856 |
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|
| 857 |
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|
| 858 |
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|
| 859 |
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"gpt_neox.layers.9.attention.query_key_value.weight": "model-00001-of-00002.safetensors",
|
| 860 |
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"gpt_neox.layers.9.attention.query_key_value.weight.absmax": "model-00001-of-00002.safetensors",
|
| 861 |
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"gpt_neox.layers.9.attention.query_key_value.weight.quant_map": "model-00001-of-00002.safetensors",
|
| 862 |
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"gpt_neox.layers.9.attention.query_key_value.weight.quant_state.bitsandbytes__fp4": "model-00001-of-00002.safetensors",
|
| 863 |
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"gpt_neox.layers.9.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
| 864 |
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"gpt_neox.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 865 |
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"gpt_neox.layers.9.mlp.dense_4h_to_h.bias": "model-00001-of-00002.safetensors",
|
| 866 |
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"gpt_neox.layers.9.mlp.dense_4h_to_h.weight": "model-00001-of-00002.safetensors",
|
| 867 |
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"gpt_neox.layers.9.mlp.dense_4h_to_h.weight.absmax": "model-00001-of-00002.safetensors",
|
| 868 |
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"gpt_neox.layers.9.mlp.dense_4h_to_h.weight.quant_map": "model-00001-of-00002.safetensors",
|
| 869 |
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"gpt_neox.layers.9.mlp.dense_4h_to_h.weight.quant_state.bitsandbytes__fp4": "model-00001-of-00002.safetensors",
|
| 870 |
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"gpt_neox.layers.9.mlp.dense_h_to_4h.bias": "model-00001-of-00002.safetensors",
|
| 871 |
+
"gpt_neox.layers.9.mlp.dense_h_to_4h.weight": "model-00001-of-00002.safetensors",
|
| 872 |
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"gpt_neox.layers.9.mlp.dense_h_to_4h.weight.absmax": "model-00001-of-00002.safetensors",
|
| 873 |
+
"gpt_neox.layers.9.mlp.dense_h_to_4h.weight.quant_map": "model-00001-of-00002.safetensors",
|
| 874 |
+
"gpt_neox.layers.9.mlp.dense_h_to_4h.weight.quant_state.bitsandbytes__fp4": "model-00001-of-00002.safetensors",
|
| 875 |
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"gpt_neox.layers.9.post_attention_layernorm.bias": "model-00001-of-00002.safetensors",
|
| 876 |
+
"gpt_neox.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors"
|
| 877 |
+
}
|
| 878 |
+
}
|
smash_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
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|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"api_key": null,
|
| 3 |
+
"verify_url": "http://johnrachwan.pythonanywhere.com",
|
| 4 |
+
"smash_config": {
|
| 5 |
+
"pruners": "None",
|
| 6 |
+
"pruning_ratio": 0.0,
|
| 7 |
+
"factorizers": "None",
|
| 8 |
+
"quantizers": "['llm-int8']",
|
| 9 |
+
"weight_quantization_bits": 4,
|
| 10 |
+
"output_deviation": 0.005,
|
| 11 |
+
"compilers": "None",
|
| 12 |
+
"static_batch": true,
|
| 13 |
+
"static_shape": true,
|
| 14 |
+
"controlnet": "None",
|
| 15 |
+
"unet_dim": 4,
|
| 16 |
+
"device": "cuda",
|
| 17 |
+
"cache_dir": "/ceph/hdd/staff/charpent/.cache/models0bym86_d",
|
| 18 |
+
"batch_size": 1,
|
| 19 |
+
"model_name": "EleutherAI/pythia-12b",
|
| 20 |
+
"task": "text_text_generation",
|
| 21 |
+
"max_batch_size": 1,
|
| 22 |
+
"qtype_weight": "torch.qint8",
|
| 23 |
+
"qtype_activation": "torch.quint8",
|
| 24 |
+
"qobserver": "<class 'torch.ao.quantization.observer.MinMaxObserver'>",
|
| 25 |
+
"qscheme": "torch.per_tensor_symmetric",
|
| 26 |
+
"qconfig": "x86",
|
| 27 |
+
"group_size": 128,
|
| 28 |
+
"damp_percent": 0.1,
|
| 29 |
+
"save_load_fn": "bitsandbytes"
|
| 30 |
+
}
|
| 31 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,23 @@
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<|endoftext|>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"eos_token": {
|
| 10 |
+
"content": "<|endoftext|>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"unk_token": {
|
| 17 |
+
"content": "<|endoftext|>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
}
|
| 23 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,215 @@
|
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|
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|
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|
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|
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|
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|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
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|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
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|
| 5 |
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"added_tokens_decoder": {
|
| 6 |
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"0": {
|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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},
|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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"special": true
|
| 21 |
+
},
|
| 22 |
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"50254": {
|
| 23 |
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"content": " ",
|
| 24 |
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|
| 25 |
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"normalized": true,
|
| 26 |
+
"rstrip": false,
|
| 27 |
+
"single_word": false,
|
| 28 |
+
"special": false
|
| 29 |
+
},
|
| 30 |
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"50255": {
|
| 31 |
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"content": " ",
|
| 32 |
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"lstrip": false,
|
| 33 |
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|
| 34 |
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"rstrip": false,
|
| 35 |
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"single_word": false,
|
| 36 |
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"special": false
|
| 37 |
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},
|
| 38 |
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"50256": {
|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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"50257": {
|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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"special": false
|
| 53 |
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|
| 54 |
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"50258": {
|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
+
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|
| 59 |
+
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|
| 60 |
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"special": false
|
| 61 |
+
},
|
| 62 |
+
"50259": {
|
| 63 |
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"content": " ",
|
| 64 |
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"lstrip": false,
|
| 65 |
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"normalized": true,
|
| 66 |
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"rstrip": false,
|
| 67 |
+
"single_word": false,
|
| 68 |
+
"special": false
|
| 69 |
+
},
|
| 70 |
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"50260": {
|
| 71 |
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"content": " ",
|
| 72 |
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"lstrip": false,
|
| 73 |
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|
| 74 |
+
"rstrip": false,
|
| 75 |
+
"single_word": false,
|
| 76 |
+
"special": false
|
| 77 |
+
},
|
| 78 |
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"50261": {
|
| 79 |
+
"content": " ",
|
| 80 |
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"lstrip": false,
|
| 81 |
+
"normalized": true,
|
| 82 |
+
"rstrip": false,
|
| 83 |
+
"single_word": false,
|
| 84 |
+
"special": false
|
| 85 |
+
},
|
| 86 |
+
"50262": {
|
| 87 |
+
"content": " ",
|
| 88 |
+
"lstrip": false,
|
| 89 |
+
"normalized": true,
|
| 90 |
+
"rstrip": false,
|
| 91 |
+
"single_word": false,
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