From 253da9a8d063c2b68a605b9cecd35e69c5e3028f Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 8 Sep 2026 13:04:22 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN Source: Original Platform --- .gitattributes | 36 + Notice | 1 + README.md | 97 ++ USE_POLICY.md | 73 ++ config.json | 53 + generation_config.json | 11 + inference_vLLM.ipynb | 576 +++++++++ model-00001-of-00009.safetensors | 3 + model-00002-of-00009.safetensors | 3 + model-00003-of-00009.safetensors | 3 + model-00004-of-00009.safetensors | 3 + model-00005-of-00009.safetensors | 3 + model-00006-of-00009.safetensors | 3 + model-00007-of-00009.safetensors | 3 + model-00008-of-00009.safetensors | 3 + model-00009-of-00009.safetensors | 3 + model.safetensors.index.json | 1850 ++++++++++++++++++++++++++ special_tokens_map.json | 17 + tokenizer.json | 3 + tokenizer_config.json | 2064 ++++++++++++++++++++++++++++++ 20 files changed, 4808 insertions(+) create mode 100644 .gitattributes create mode 100644 Notice create mode 100644 README.md create mode 100644 USE_POLICY.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 inference_vLLM.ipynb create mode 100644 model-00001-of-00009.safetensors create mode 100644 model-00002-of-00009.safetensors create mode 100644 model-00003-of-00009.safetensors create mode 100644 model-00004-of-00009.safetensors create mode 100644 model-00005-of-00009.safetensors create mode 100644 model-00006-of-00009.safetensors create mode 100644 model-00007-of-00009.safetensors create mode 100644 model-00008-of-00009.safetensors create mode 100644 model-00009-of-00009.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/Notice b/Notice new file mode 100644 index 0000000..529d357 --- /dev/null +++ b/Notice @@ -0,0 +1 @@ +Llama 3.3 is licensed under the Llama 3.3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..501173f --- /dev/null +++ b/README.md @@ -0,0 +1,97 @@ +--- +license: mit +base_model: +- meta-llama/Llama-3.3-70B-Instruct +language: +- ja +- en +pipeline_tag: text-generation +library_name: transformers +tags: +- llama-3 +- pytorch +- llama-3.3 +- autoawq +- meta +--- + +# kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN + +## model information +[Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)を[AutoAWQ](https://github.com/casper-hansen/AutoAWQ)で4bit 量子化したモデル。量子化の際のキャリブレーションデータに日本語と英語を含むデータを使用。 +A model of Llama-3.3-70B-Instruct quantized to 4 bits using AutoAWQ. Calibration data containing Japanese and English was used during the quantization process. + +## usage +### transformers +```python +from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer + +tokenizer = AutoTokenizer.from_pretrained("kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN") +model = AutoModelForCausalLM.from_pretrained("kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN") +model.to("cuda") + +chat = [ + {"role": "system", "content": "あなたは日本語で応答するAIチャットボットです。ユーザをサポートしてください。"}, + {"role": "user", "content": "plotly.graph_objectsを使って散布図を作るサンプルコードを書いてください。"} +] +prompt = tokenizer.apply_chat_template( + chat, + tokenize=False, + add_generation_prompt=True +) +inputs = tokenizer(prompt, return_tensors="pt") +inputs = inputs.to("cuda") +streamer = TextStreamer(tokenizer) + +output = model.generate(**inputs, streamer=streamer, max_new_tokens=1024) +``` +このコードはA100インスタンスの[Google Colab](https://colab.research.google.com/drive/1NSWV6MMisTlN5ELN42VPMLRH9ahAfNrJ?usp=sharing) でも動かせます。 +This code can also run on Google Colab with an A100 instance. + +### vLLM +```python +from vllm import LLM, SamplingParams + +llm = LLM( + model="kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN", + tensor_parallel_size=1, + gpu_memory_utilization=0.97, + quantization="awq" +) +tokenizer = llm.get_tokenizer() + +messages = [ + {"role": "system", "content": "あなたは日本語で応答するAIチャットボットです。ユーザをサポートしてください。"}, + {"role": "user", "content": "plotly.graph_objectsを使って散布図を作るサンプルコードを書いてください。"}, +] + +prompt = tokenizer.apply_chat_template( + messages, + tokenize=False, + add_generation_prompt=True +) + +sampling_params = SamplingParams( + temperature=0.6, + top_p=0.9, + max_tokens=1024 +) + +outputs = llm.generate(prompt, sampling_params) +print(outputs[0].outputs[0].text) +``` +H100 (94GB)を1基積んだインスタンスでの実行はこちらの[notebook](https://huggingface.co/kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN/blob/main/inference_vLLM.ipynb)をご覧ください。 +Please refer to this notebook for execution on an instance equipped with a single H100 (94GB). + +## calibration data +以下のデータセットから512個のデータ，プロンプトを抽出。1つのデータのトークン数は最大350制限。 +Extract 512 data points and prompts from the following dataset. The maximum token limit per data point is 350. +- [TFMC/imatrix-dataset-for-japanese-llm](https://huggingface.co/datasets/TFMC/imatrix-dataset-for-japanese-llm) +- [meta-math/MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA) +- [m-a-p/CodeFeedback-Filtered-Instruction](https://huggingface.co/datasets/m-a-p/CodeFeedback-Filtered-Instruction) +- [kunishou/databricks-dolly-15k-ja](https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja) +- その他日本語版・英語版のwikipedia記事から作成したオリジナルデータ，有害プロンプト回避のためのオリジナルデータを使用。 Original data created from Japanese and English Wikipedia articles, as well as original data for avoiding harmful prompts, is used. + +## License +[MIT License](https://opensource.org/license/mit)を適用する。ただし量子化のベースモデルに適用されている[Llama 3.3 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE)に従ってください。 +The MIT License is applied. However, obey the Llama 3.3 Community License Agreement applied to the base model of quantization. \ No newline at end of file diff --git a/USE_POLICY.md b/USE_POLICY.md new file mode 100644 index 0000000..2b5602b --- /dev/null +++ b/USE_POLICY.md @@ -0,0 +1,73 @@ +**Llama 3.3** **Acceptable Use Policy** + +Meta is committed to promoting safe and fair use of its tools and features, including Llama 3.3. If you access or use Llama 3.3, you agree to this Acceptable Use Policy (“**Policy**”). The most recent copy of this policy can be found at [https://www.llama.com/llama3\_3/use-policy](https://www.llama.com/llama3_3/use-policy). + +**Prohibited Uses** + +We want everyone to use Llama 3.3 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.3 to: + +1. Violate the law or others’ rights, including to: + + 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as: + 1. Violence or terrorism + 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material + 3. Human trafficking, exploitation, and sexual violence + 4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials. + 5. Sexual solicitation + 6. Any other criminal activity + + 2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals + + 3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services + + 4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices + + 5. Collect, process, disclose, generate, or infer private or sensitive information about individuals, including information about individuals’ identity, health, or demographic information, unless you have obtained the right to do so in accordance with applicable law + + 6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials + + 7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system + + 8. Engage in any action, or facilitate any action, to intentionally circumvent or remove usage restrictions or other safety measures, or to enable functionality disabled by Meta  + +2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.3 related to the following: + + 1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State or to the U.S. Biological Weapons Anti-Terrorism Act of 1989 or the Chemical Weapons Convention Implementation Act of 1997 + + 2. Guns and illegal weapons (including weapon development) + + 3. Illegal drugs and regulated/controlled substances + + 4. Operation of critical infrastructure, transportation technologies, or heavy machinery + + 5. Self-harm or harm to others, including suicide, cutting, and eating disorders + + 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual + +3. Intentionally deceive or mislead others, including use of Llama 3.3 related to the following: + + 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation + + 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content + + 3. Generating, promoting, or further distributing spam + + 4. Impersonating another individual without consent, authorization, or legal right + + 5. Representing that the use of Llama 3.3 or outputs are human-generated + + 6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement  + +4. Fail to appropriately disclose to end users any known dangers of your AI system + +5. Interact with third party tools, models, or software designed to generate unlawful content or engage in unlawful or harmful conduct and/or represent that the outputs of such tools, models, or software are associated with Meta or Llama 3.3 + +With respect to any multimodal models included in Llama 3.3, the rights granted under Section 1(a) of the Llama 3.3 Community License Agreement are not being granted to you if you are an individual domiciled in, or a company with a principal place of business in, the European Union. This restriction does not apply to end users of a product or service that incorporates any such multimodal models. + +Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means: + +* Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ) +* Reporting risky content generated by the model: [developers.facebook.com/llama\_output\_feedback](http://developers.facebook.com/llama_output_feedback) +* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info) +* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama 3.3: LlamaUseReport@meta.com + diff --git a/config.json b/config.json new file mode 100644 index 0000000..09f319e --- /dev/null +++ b/config.json @@ -0,0 +1,53 @@ +{ + "_name_or_path": "kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 128000, + "eos_token_id": [ + 128001, + 128008, + 128009 + ], + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 8192, + "initializer_range": 0.02, + "intermediate_size": 28672, + "max_position_embeddings": 131072, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 64, + "num_hidden_layers": 80, + "num_key_value_heads": 8, + "pretraining_tp": 1, + "quantization_config": { + "backend": "autoawq", + "bits": 4, + "do_fuse": false, + "exllama_config": null, + "fuse_max_seq_len": null, + "group_size": 128, + "modules_to_fuse": null, + "modules_to_not_convert": null, + "quant_method": "awq", + "version": "gemm", + "zero_point": true + }, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 8.0, + "high_freq_factor": 4.0, + "low_freq_factor": 1.0, + "original_max_position_embeddings": 8192, + "rope_type": "llama3" + }, + "rope_theta": 500000.0, + "tie_word_embeddings": false, + "torch_dtype": "float16", + "transformers_version": "4.47.0.dev0", + "use_cache": true, + "vocab_size": 128256 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..c81cda4 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,11 @@ +{ + "_from_model_config": true, + "bos_token_id": 128000, + "eos_token_id": [ + 128001, + 128008, + 128009 + ], + "transformers_version": "4.47.0.dev0", + "use_cache": false +} diff --git a/inference_vLLM.ipynb b/inference_vLLM.ipynb new file mode 100644 index 0000000..6539ace --- /dev/null +++ b/inference_vLLM.ipynb @@ -0,0 +1,576 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "97626fd6-6fcc-4d8f-a5af-40441e46f98b", + "metadata": {}, + 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installation: typing_extensions 4.9.0\n", + " Uninstalling typing_extensions-4.9.0:\n", + " Successfully uninstalled typing_extensions-4.9.0\n", + " Attempting uninstall: triton\n", + " Found existing installation: triton 3.0.0\n", + " Uninstalling triton-3.0.0:\n", + " Successfully uninstalled triton-3.0.0\n", + " Attempting uninstall: sympy\n", + " Found existing installation: sympy 1.12\n", + " Uninstalling sympy-1.12:\n", + " Successfully uninstalled sympy-1.12\n", + " Attempting uninstall: pillow\n", + " Found existing installation: pillow 10.2.0\n", + " Uninstalling pillow-10.2.0:\n", + " Successfully uninstalled pillow-10.2.0\n", + " Attempting uninstall: nvidia-nvtx-cu12\n", + " Found existing installation: nvidia-nvtx-cu12 12.4.99\n", + " Uninstalling nvidia-nvtx-cu12-12.4.99:\n", + " Successfully uninstalled nvidia-nvtx-cu12-12.4.99\n", + " Attempting uninstall: nvidia-nvjitlink-cu12\n", + " Found existing installation: nvidia-nvjitlink-cu12 12.4.99\n", + " Uninstalling nvidia-nvjitlink-cu12-12.4.99:\n", + " Successfully uninstalled nvidia-nvjitlink-cu12-12.4.99\n", + " Attempting uninstall: nvidia-nccl-cu12\n", + " Found existing installation: nvidia-nccl-cu12 2.20.5\n", + " Uninstalling nvidia-nccl-cu12-2.20.5:\n", + " Successfully uninstalled nvidia-nccl-cu12-2.20.5\n", + " Attempting uninstall: nvidia-curand-cu12\n", + " Found existing installation: nvidia-curand-cu12 10.3.5.119\n", + " Uninstalling nvidia-curand-cu12-10.3.5.119:\n", + " Successfully uninstalled nvidia-curand-cu12-10.3.5.119\n", + " Attempting uninstall: nvidia-cufft-cu12\n", + " Found existing installation: nvidia-cufft-cu12 11.2.0.44\n", + " Uninstalling nvidia-cufft-cu12-11.2.0.44:\n", + " Successfully uninstalled nvidia-cufft-cu12-11.2.0.44\n", + " Attempting uninstall: nvidia-cuda-runtime-cu12\n", + " Found existing installation: nvidia-cuda-runtime-cu12 12.4.99\n", + " Uninstalling nvidia-cuda-runtime-cu12-12.4.99:\n", + " Successfully uninstalled nvidia-cuda-runtime-cu12-12.4.99\n", + " Attempting uninstall: nvidia-cuda-nvrtc-cu12\n", + " Found existing installation: nvidia-cuda-nvrtc-cu12 12.4.99\n", + " Uninstalling nvidia-cuda-nvrtc-cu12-12.4.99:\n", + " Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.4.99\n", + " Attempting uninstall: nvidia-cuda-cupti-cu12\n", + " Found existing installation: nvidia-cuda-cupti-cu12 12.4.99\n", + " Uninstalling nvidia-cuda-cupti-cu12-12.4.99:\n", + " Successfully uninstalled nvidia-cuda-cupti-cu12-12.4.99\n", + " Attempting uninstall: nvidia-cublas-cu12\n", + " Found existing installation: nvidia-cublas-cu12 12.4.2.65\n", + " Uninstalling nvidia-cublas-cu12-12.4.2.65:\n", + " Successfully uninstalled nvidia-cublas-cu12-12.4.2.65\n", + " Attempting uninstall: nvidia-cusparse-cu12\n", + " Found existing installation: nvidia-cusparse-cu12 12.3.0.142\n", + " Uninstalling nvidia-cusparse-cu12-12.3.0.142:\n", + " Successfully uninstalled nvidia-cusparse-cu12-12.3.0.142\n", + " Attempting uninstall: nvidia-cusolver-cu12\n", + " Found existing installation: nvidia-cusolver-cu12 11.6.0.99\n", + " Uninstalling nvidia-cusolver-cu12-11.6.0.99:\n", + " Successfully uninstalled nvidia-cusolver-cu12-11.6.0.99\n", + " Attempting uninstall: torch\n", + " Found existing installation: torch 2.4.1+cu124\n", + " Uninstalling torch-2.4.1+cu124:\n", + " Successfully uninstalled torch-2.4.1+cu124\n", + " Attempting uninstall: torchvision\n", + " Found existing installation: torchvision 0.19.1+cu124\n", + " Uninstalling torchvision-0.19.1+cu124:\n", + " Successfully uninstalled torchvision-0.19.1+cu124\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "torchaudio 2.4.1+cu124 requires torch==2.4.1, but you have torch 2.5.1 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed annotated-types-0.7.0 click-8.1.7 cloudpickle-3.1.0 compressed-tensors-0.8.0 diskcache-5.6.3 einops-0.8.0 fastapi-0.115.6 gguf-0.10.0 httptools-0.6.4 interegular-0.3.3 jiter-0.8.0 lark-1.2.2 llvmlite-0.43.0 lm-format-enforcer-0.10.9 mistral-common-1.5.1 msgpack-1.1.0 msgspec-0.18.6 numba-0.60.0 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-ml-py-12.560.30 nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 openai-1.57.0 opencv-python-headless-4.10.0.84 outlines-0.0.46 partial-json-parser-0.2.1.1.post4 pillow-10.4.0 prometheus-fastapi-instrumentator-7.0.0 protobuf-5.29.1 py-cpuinfo-9.0.0 pyairports-2.1.1 pycountry-24.6.1 pydantic-2.10.3 pydantic-core-2.27.1 python-dotenv-1.0.1 ray-2.40.0 sentencepiece-0.2.0 starlette-0.41.3 sympy-1.13.1 tiktoken-0.7.0 torch-2.5.1 torchvision-0.20.1 triton-3.1.0 typing-extensions-4.12.2 uvicorn-0.32.1 uvloop-0.21.0 vllm-0.6.4.post1 watchfiles-1.0.0 websockets-14.1 xformers-0.0.28.post3\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable.It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.\u001b[0m\u001b[33m\n", + "\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n" + ] + } + ], + "source": [ + "!pip install vllm autoawq" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "56a955b4-c65a-4146-9281-ebcb4ee81209", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sun Dec 8 00:57:27 2024 \n", + "+-----------------------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 565.57.01 Driver Version: 565.57.01 CUDA Version: 12.7 |\n", + "|-----------------------------------------+------------------------+----------------------+\n", + "| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n", + "| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n", + "| | | MIG M. |\n", + "|=========================================+========================+======================|\n", + "| 0 NVIDIA H100 NVL On | 00000000:AE:00.0 Off | 0 |\n", + "| N/A 32C P0 60W / 310W | 1MiB / 95830MiB | 0% Default |\n", + "| | | Disabled |\n", + "+-----------------------------------------+------------------------+----------------------+\n", + " \n", + "+-----------------------------------------------------------------------------------------+\n", + "| Processes: |\n", + "| GPU GI CI PID Type Process name GPU Memory |\n", + "| ID ID Usage |\n", + "|=========================================================================================|\n", + "| No running processes found |\n", + "+-----------------------------------------------------------------------------------------+\n" + ] + } + ], + "source": [ + "!nvidia-smi" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "8f40dc17-a05a-466f-85d9-5bfa473c133b", + "metadata": {}, + "outputs": [], + "source": [ + "from vllm import LLM, SamplingParams" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "ecf09ccb-b47b-40bc-a501-ded94239465d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "INFO 12-08 01:02:42 config.py:350] This model supports multiple tasks: {'generate', 'embedding'}. Defaulting to 'generate'.\n", + "INFO 12-08 01:02:42 awq_marlin.py:113] Detected that the model can run with awq_marlin, however you specified quantization=awq explicitly, so forcing awq. Use quantization=awq_marlin for faster inference\n", + "WARNING 12-08 01:02:42 config.py:428] awq quantization is not fully optimized yet. The speed can be slower than non-quantized models.\n", + "WARNING 12-08 01:02:42 arg_utils.py:1013] Chunked prefill is enabled by default for models with max_model_len > 32K. Currently, chunked prefill might not work with some features or models. If you encounter any issues, please disable chunked prefill by setting --enable-chunked-prefill=False.\n", + "INFO 12-08 01:02:42 config.py:1136] Chunked prefill is enabled with max_num_batched_tokens=512.\n", + "INFO 12-08 01:02:42 llm_engine.py:249] Initializing an LLM engine (v0.6.4.post1) with config: model='kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN', speculative_config=None, tokenizer='kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=131072, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=awq, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN, num_scheduler_steps=1, chunked_prefill_enabled=True multi_step_stream_outputs=True, enable_prefix_caching=False, use_async_output_proc=True, use_cached_outputs=False, chat_template_text_format=string, mm_processor_kwargs=None, pooler_config=None)\n", + "INFO 12-08 01:02:44 selector.py:135] Using Flash Attention backend.\n", + "INFO 12-08 01:02:44 model_runner.py:1072] Starting to load model kishizaki-sci/Llama-3.3-70B-Instruct-AWQ-4bit-JP-EN...\n", + "INFO 12-08 01:02:45 weight_utils.py:243] Using model weights format ['*.safetensors']\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "1b29444155504b5eaadb35d628775f18", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Loading safetensors checkpoint shards: 0% 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"single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "extra_special_tokens": {}, + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|eot_id|>", + "tokenizer_class": "PreTrainedTokenizerFast" +}