d3988155a965b05007aa75cfb02e3467c56bb576dbc827ad037929ce4a2f9586
Browse files- README.md +85 -0
- config.json +38 -0
- generation_config.json +8 -0
- smash_config.json +31 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +2461 -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: 01-ai/Yi-1.5-6B-Chat
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metrics:
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- memory_disk
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- memory_inference
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| 7 |
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- inference_latency
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| 8 |
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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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| 24 |
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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/rskEr4BZJx)
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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 |
+
- 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 awq.
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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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- ***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 01-ai/Yi-1.5-6B-Chat 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 autoawq
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```
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2. Load & run the model.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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| 63 |
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from awq import AutoAWQForCausalLM
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| 64 |
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model = AutoAWQForCausalLM.from_quantized("PrunaAI/01-ai-Yi-1.5-6B-Chat-AWQ-4bit-smashed", trust_remote_code=True, device_map='auto')
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tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-1.5-6B-Chat")
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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 01-ai/Yi-1.5-6B-Chat 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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## Want to compress other models?
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| 83 |
+
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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/models6zuz3qkkccfelpfr",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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| 7 |
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"attention_dropout": 0.0,
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| 8 |
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"bos_token_id": 1,
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"eos_token_id": 2,
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| 10 |
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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| 14 |
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"max_position_embeddings": 4096,
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| 15 |
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"mlp_bias": false,
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| 16 |
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"model_type": "llama",
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| 17 |
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"num_attention_heads": 32,
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| 18 |
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"num_hidden_layers": 32,
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| 19 |
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"num_key_value_heads": 4,
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| 20 |
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"pad_token_id": 0,
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| 21 |
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"pretraining_tp": 1,
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| 22 |
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"quantization_config": {
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"bits": 4,
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| 24 |
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"group_size": 128,
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| 25 |
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"modules_to_not_convert": null,
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"quant_method": "awq",
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"version": "gemm",
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| 28 |
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"zero_point": true
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},
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"rms_norm_eps": 1e-06,
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| 31 |
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"rope_scaling": null,
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| 32 |
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"rope_theta": 5000000.0,
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| 33 |
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"tie_word_embeddings": false,
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| 34 |
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"torch_dtype": "float16",
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| 35 |
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"transformers_version": "4.42.4",
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"use_cache": false,
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"vocab_size": 64000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"do_sample": true,
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| 5 |
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"eos_token_id": 2,
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| 6 |
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"pad_token_id": 0,
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"transformers_version": "4.42.4"
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}
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smash_config.json
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{
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| 2 |
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"api_key": null,
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| 3 |
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"verify_url": "http://johnrachwan.pythonanywhere.com",
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| 4 |
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"smash_config": {
|
| 5 |
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"pruners": "None",
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| 6 |
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"pruning_ratio": 0.0,
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| 7 |
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"factorizers": "None",
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| 8 |
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"quantizers": "['awq']",
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| 9 |
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"weight_quantization_bits": 4,
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| 10 |
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"output_deviation": 0.005,
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| 11 |
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"compilers": "None",
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| 12 |
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"static_batch": true,
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"static_shape": true,
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| 14 |
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"controlnet": "None",
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| 15 |
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"unet_dim": 4,
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"device": "cuda",
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| 17 |
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"cache_dir": "/ceph/hdd/staff/charpent/.cache/models6zuz3qkk",
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| 18 |
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"batch_size": 1,
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| 19 |
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"model_name": "01-ai/Yi-1.5-6B-Chat",
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| 20 |
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"task": "text_text_generation",
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| 21 |
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"max_batch_size": 1,
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| 22 |
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"qtype_weight": "torch.qint8",
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| 23 |
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"qtype_activation": "torch.quint8",
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| 24 |
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"qobserver": "<class 'torch.ao.quantization.observer.MinMaxObserver'>",
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| 25 |
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"qscheme": "torch.per_tensor_symmetric",
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| 26 |
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"qconfig": "x86",
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| 27 |
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"group_size": 128,
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| 28 |
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"damp_percent": 0.1,
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| 29 |
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"save_load_fn": "hf-awq"
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| 30 |
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}
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}
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|im_end|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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| 24 |
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"content": "<unk>",
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"lstrip": false,
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| 26 |
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": true,
|
| 5 |
+
"added_tokens_decoder": {
|
| 6 |
+
"0": {
|
| 7 |
+
"content": "<unk>",
|
| 8 |
+
"lstrip": false,
|
| 9 |
+
"normalized": true,
|
| 10 |
+
"rstrip": false,
|
| 11 |
+
"single_word": false,
|
| 12 |
+
"special": true
|
| 13 |
+
},
|
| 14 |
+
"1": {
|
| 15 |
+
"content": "<|startoftext|>",
|
| 16 |
+
"lstrip": false,
|
| 17 |
+
"normalized": true,
|
| 18 |
+
"rstrip": false,
|
| 19 |
+
"single_word": false,
|
| 20 |
+
"special": true
|
| 21 |
+
},
|
| 22 |
+
"2": {
|
| 23 |
+
"content": "<|endoftext|>",
|
| 24 |
+
"lstrip": false,
|
| 25 |
+
"normalized": true,
|
| 26 |
+
"rstrip": false,
|
| 27 |
+
"single_word": false,
|
| 28 |
+
"special": true
|
| 29 |
+
},
|
| 30 |
+
"3": {
|
| 31 |
+
"content": "<|Human|>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": true
|
| 37 |
+
},
|
| 38 |
+
"4": {
|
| 39 |
+
"content": "<|Assistant|>",
|
| 40 |
+
"lstrip": false,
|
| 41 |
+
"normalized": false,
|
| 42 |
+
"rstrip": false,
|
| 43 |
+
"single_word": false,
|
| 44 |
+
"special": true
|
| 45 |
+
},
|
| 46 |
+
"5": {
|
| 47 |
+
"content": "<|System|>",
|
| 48 |
+
"lstrip": false,
|
| 49 |
+
"normalized": false,
|
| 50 |
+
"rstrip": false,
|
| 51 |
+
"single_word": false,
|
| 52 |
+
"special": true
|
| 53 |
+
},
|
| 54 |
+
"6": {
|
| 55 |
+
"content": "<|im_start|>",
|
| 56 |
+
"lstrip": false,
|
| 57 |
+
"normalized": false,
|
| 58 |
+
"rstrip": false,
|
| 59 |
+
"single_word": false,
|
| 60 |
+
"special": false
|
| 61 |
+
},
|
| 62 |
+
"7": {
|
| 63 |
+
"content": "<|im_end|>",
|
| 64 |
+
"lstrip": false,
|
| 65 |
+
"normalized": false,
|
| 66 |
+
"rstrip": false,
|
| 67 |
+
"single_word": false,
|
| 68 |
+
"special": true
|
| 69 |
+
},
|
| 70 |
+
"8": {
|
| 71 |
+
"content": "<|im_sep|>",
|
| 72 |
+
"lstrip": false,
|
| 73 |
+
"normalized": false,
|
| 74 |
+
"rstrip": false,
|
| 75 |
+
"single_word": false,
|
| 76 |
+
"special": false
|
| 77 |
+
},
|
| 78 |
+
"9": {
|
| 79 |
+
"content": "<|reserved003|>",
|
| 80 |
+
"lstrip": false,
|
| 81 |
+
"normalized": false,
|
| 82 |
+
"rstrip": false,
|
| 83 |
+
"single_word": false,
|
| 84 |
+
"special": true
|
| 85 |
+
},
|
| 86 |
+
"10": {
|
| 87 |
+
"content": "<|reserved004|>",
|
| 88 |
+
"lstrip": false,
|
| 89 |
+
"normalized": false,
|
| 90 |
+
"rstrip": false,
|
| 91 |
+
"single_word": false,
|
| 92 |
+
"special": true
|
| 93 |
+
},
|
| 94 |
+
"11": {
|
| 95 |
+
"content": "<|reserved005|>",
|
| 96 |
+
"lstrip": false,
|
| 97 |
+
"normalized": false,
|
| 98 |
+
"rstrip": false,
|
| 99 |
+
"single_word": false,
|
| 100 |
+
"special": true
|
| 101 |
+
},
|
| 102 |
+
"12": {
|
| 103 |
+
"content": "<|reserved006|>",
|
| 104 |
+
"lstrip": false,
|
| 105 |
+
"normalized": false,
|
| 106 |
+
"rstrip": false,
|
| 107 |
+
"single_word": false,
|
| 108 |
+
"special": true
|
| 109 |
+
},
|
| 110 |
+
"13": {
|
| 111 |
+
"content": "<|reserved007|>",
|
| 112 |
+
"lstrip": false,
|
| 113 |
+
"normalized": false,
|
| 114 |
+
"rstrip": false,
|
| 115 |
+
"single_word": false,
|
| 116 |
+
"special": true
|
| 117 |
+
},
|
| 118 |
+
"14": {
|
| 119 |
+
"content": "<fim_prefix>",
|
| 120 |
+
"lstrip": false,
|
| 121 |
+
"normalized": false,
|
| 122 |
+
"rstrip": false,
|
| 123 |
+
"single_word": false,
|
| 124 |
+
"special": false
|
| 125 |
+
},
|
| 126 |
+
"15": {
|
| 127 |
+
"content": "<fim_middle>",
|
| 128 |
+
"lstrip": false,
|
| 129 |
+
"normalized": false,
|
| 130 |
+
"rstrip": false,
|
| 131 |
+
"single_word": false,
|
| 132 |
+
"special": false
|
| 133 |
+
},
|
| 134 |
+
"16": {
|
| 135 |
+
"content": "<fim_suffix>",
|
| 136 |
+
"lstrip": false,
|
| 137 |
+
"normalized": false,
|
| 138 |
+
"rstrip": false,
|
| 139 |
+
"single_word": false,
|
| 140 |
+
"special": false
|
| 141 |
+
},
|
| 142 |
+
"17": {
|
| 143 |
+
"content": "<fim_pad>",
|
| 144 |
+
"lstrip": false,
|
| 145 |
+
"normalized": false,
|
| 146 |
+
"rstrip": false,
|
| 147 |
+
"single_word": false,
|
| 148 |
+
"special": false
|
| 149 |
+
},
|
| 150 |
+
"18": {
|
| 151 |
+
"content": "<filename>",
|
| 152 |
+
"lstrip": false,
|
| 153 |
+
"normalized": false,
|
| 154 |
+
"rstrip": false,
|
| 155 |
+
"single_word": false,
|
| 156 |
+
"special": false
|
| 157 |
+
},
|
| 158 |
+
"19": {
|
| 159 |
+
"content": "<gh_stars>",
|
| 160 |
+
"lstrip": false,
|
| 161 |
+
"normalized": false,
|
| 162 |
+
"rstrip": false,
|
| 163 |
+
"single_word": false,
|
| 164 |
+
"special": false
|
| 165 |
+
},
|
| 166 |
+
"20": {
|
| 167 |
+
"content": "<issue_start>",
|
| 168 |
+
"lstrip": false,
|
| 169 |
+
"normalized": false,
|
| 170 |
+
"rstrip": false,
|
| 171 |
+
"single_word": false,
|
| 172 |
+
"special": false
|
| 173 |
+
},
|
| 174 |
+
"21": {
|
| 175 |
+
"content": "<issue_comment>",
|
| 176 |
+
"lstrip": false,
|
| 177 |
+
"normalized": false,
|
| 178 |
+
"rstrip": false,
|
| 179 |
+
"single_word": false,
|
| 180 |
+
"special": false
|
| 181 |
+
},
|
| 182 |
+
"22": {
|
| 183 |
+
"content": "<issue_closed>",
|
| 184 |
+
"lstrip": false,
|
| 185 |
+
"normalized": false,
|
| 186 |
+
"rstrip": false,
|
| 187 |
+
"single_word": false,
|
| 188 |
+
"special": false
|
| 189 |
+
},
|
| 190 |
+
"23": {
|
| 191 |
+
"content": "<jupyter_start>",
|
| 192 |
+
"lstrip": false,
|
| 193 |
+
"normalized": false,
|
| 194 |
+
"rstrip": false,
|
| 195 |
+
"single_word": false,
|
| 196 |
+
"special": false
|
| 197 |
+
},
|
| 198 |
+
"24": {
|
| 199 |
+
"content": "<jupyter_text>",
|
| 200 |
+
"lstrip": false,
|
| 201 |
+
"normalized": false,
|
| 202 |
+
"rstrip": false,
|
| 203 |
+
"single_word": false,
|
| 204 |
+
"special": false
|
| 205 |
+
},
|
| 206 |
+
"25": {
|
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"special": false
|
| 2341 |
+
},
|
| 2342 |
+
"292": {
|
| 2343 |
+
"content": "<|unused147|>",
|
| 2344 |
+
"lstrip": false,
|
| 2345 |
+
"normalized": false,
|
| 2346 |
+
"rstrip": false,
|
| 2347 |
+
"single_word": false,
|
| 2348 |
+
"special": false
|
| 2349 |
+
},
|
| 2350 |
+
"293": {
|
| 2351 |
+
"content": "<|unused148|>",
|
| 2352 |
+
"lstrip": false,
|
| 2353 |
+
"normalized": false,
|
| 2354 |
+
"rstrip": false,
|
| 2355 |
+
"single_word": false,
|
| 2356 |
+
"special": false
|
| 2357 |
+
},
|
| 2358 |
+
"294": {
|
| 2359 |
+
"content": "<|unused149|>",
|
| 2360 |
+
"lstrip": false,
|
| 2361 |
+
"normalized": false,
|
| 2362 |
+
"rstrip": false,
|
| 2363 |
+
"single_word": false,
|
| 2364 |
+
"special": false
|
| 2365 |
+
},
|
| 2366 |
+
"295": {
|
| 2367 |
+
"content": "<|unused150|>",
|
| 2368 |
+
"lstrip": false,
|
| 2369 |
+
"normalized": false,
|
| 2370 |
+
"rstrip": false,
|
| 2371 |
+
"single_word": false,
|
| 2372 |
+
"special": false
|
| 2373 |
+
},
|
| 2374 |
+
"296": {
|
| 2375 |
+
"content": "<|unused151|>",
|
| 2376 |
+
"lstrip": false,
|
| 2377 |
+
"normalized": false,
|
| 2378 |
+
"rstrip": false,
|
| 2379 |
+
"single_word": false,
|
| 2380 |
+
"special": false
|
| 2381 |
+
},
|
| 2382 |
+
"297": {
|
| 2383 |
+
"content": "<|unused152|>",
|
| 2384 |
+
"lstrip": false,
|
| 2385 |
+
"normalized": false,
|
| 2386 |
+
"rstrip": false,
|
| 2387 |
+
"single_word": false,
|
| 2388 |
+
"special": false
|
| 2389 |
+
},
|
| 2390 |
+
"298": {
|
| 2391 |
+
"content": "<|unused153|>",
|
| 2392 |
+
"lstrip": false,
|
| 2393 |
+
"normalized": false,
|
| 2394 |
+
"rstrip": false,
|
| 2395 |
+
"single_word": false,
|
| 2396 |
+
"special": false
|
| 2397 |
+
},
|
| 2398 |
+
"299": {
|
| 2399 |
+
"content": "<|unused154|>",
|
| 2400 |
+
"lstrip": false,
|
| 2401 |
+
"normalized": false,
|
| 2402 |
+
"rstrip": false,
|
| 2403 |
+
"single_word": false,
|
| 2404 |
+
"special": false
|
| 2405 |
+
},
|
| 2406 |
+
"300": {
|
| 2407 |
+
"content": "<|unused155|>",
|
| 2408 |
+
"lstrip": false,
|
| 2409 |
+
"normalized": false,
|
| 2410 |
+
"rstrip": false,
|
| 2411 |
+
"single_word": false,
|
| 2412 |
+
"special": false
|
| 2413 |
+
},
|
| 2414 |
+
"301": {
|
| 2415 |
+
"content": "<|unused156|>",
|
| 2416 |
+
"lstrip": false,
|
| 2417 |
+
"normalized": false,
|
| 2418 |
+
"rstrip": false,
|
| 2419 |
+
"single_word": false,
|
| 2420 |
+
"special": false
|
| 2421 |
+
},
|
| 2422 |
+
"302": {
|
| 2423 |
+
"content": "<|unused157|>",
|
| 2424 |
+
"lstrip": false,
|
| 2425 |
+
"normalized": false,
|
| 2426 |
+
"rstrip": false,
|
| 2427 |
+
"single_word": false,
|
| 2428 |
+
"special": false
|
| 2429 |
+
},
|
| 2430 |
+
"303": {
|
| 2431 |
+
"content": "<|unused158|>",
|
| 2432 |
+
"lstrip": false,
|
| 2433 |
+
"normalized": false,
|
| 2434 |
+
"rstrip": false,
|
| 2435 |
+
"single_word": false,
|
| 2436 |
+
"special": false
|
| 2437 |
+
},
|
| 2438 |
+
"304": {
|
| 2439 |
+
"content": "<|unused159|>",
|
| 2440 |
+
"lstrip": false,
|
| 2441 |
+
"normalized": false,
|
| 2442 |
+
"rstrip": false,
|
| 2443 |
+
"single_word": false,
|
| 2444 |
+
"special": false
|
| 2445 |
+
}
|
| 2446 |
+
},
|
| 2447 |
+
"bos_token": "<|startoftext|>",
|
| 2448 |
+
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\\n' + content + '<|im_end|>\\n<|im_start|>assistant\\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\\n' }}{% endif %}{% endfor %}",
|
| 2449 |
+
"clean_up_tokenization_spaces": false,
|
| 2450 |
+
"eos_token": "<|im_end|>",
|
| 2451 |
+
"legacy": false,
|
| 2452 |
+
"model_max_length": 4096,
|
| 2453 |
+
"pad_token": "<unk>",
|
| 2454 |
+
"padding_side": "right",
|
| 2455 |
+
"sp_model_kwargs": {},
|
| 2456 |
+
"spaces_between_special_tokens": false,
|
| 2457 |
+
"split_special_tokens": false,
|
| 2458 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 2459 |
+
"unk_token": "<unk>",
|
| 2460 |
+
"use_default_system_prompt": false
|
| 2461 |
+
}
|