From 3cf107d1213677ed082770eb6fb448337e7705f4 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Thu, 22 Oct 2026 06:57:13 +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: RedHatAI/Qwen2.5-7B-quantized.w4a16 Source: Original Platform --- .gitattributes | 36 +++++ README.md | 223 +++++++++++++++++++++++++++++++ added_tokens.json | 24 ++++ config.json | 62 +++++++++ configuration.json | 1 + generation_config.json | 6 + merges.txt | 3 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 3 + recipe.yaml | 11 ++ special_tokens_map.json | 31 +++++ tokenizer.json | 3 + tokenizer_config.json | 3 + vocab.json | 3 + 15 files changed, 415 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 added_tokens.json create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 merges.txt create mode 100644 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.safetensors create mode 100644 model.safetensors.index.json create mode 100644 recipe.yaml create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 vocab.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/README.md b/README.md new file mode 100644 index 0000000..eec79e5 --- /dev/null +++ b/README.md @@ -0,0 +1,223 @@ +--- +license: apache-2.0 +license_link: https://huggingface.co/Qwen/Qwen2.5-7B/blob/main/LICENSE +language: +- en +pipeline_tag: text-generation +base_model: Qwen/Qwen2.5-7B +tags: +- chat +- neuralmagic +- llmcompressor +- int4 +--- + +# Qwen2.5-7B-quantized.w4a16 + +## Model Overview +- **Model Architecture:** Qwen2 + - **Input:** Text + - **Output:** Text +- **Model Optimizations:** + - **Weight quantization:** INT4 +- **Intended Use Cases:** Intended for commercial and research use multiple languages. Similarly to [Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B), this models is intended for assistant-like chat. +- **Out-of-scope:** Use in any manner that violates applicable laws or regulations (including trade compliance laws). +- **Release Date:** 10/18/2024 +- **Version:** 1.0 +- **License(s):** [apache-2.0](https://huggingface.co/Qwen/Qwen2.5-7B/blob/main/LICENSE) +- **Model Developers:** Neural Magic + +### Model Optimizations + +This model was obtained by quantizing the weights of [Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) to INT4 data type. +This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%. + +Only the weights of the linear operators within transformers blocks are quantized. +Weights are quantized using a symmetric per-group scheme, with group size 128. +The [GPTQ](https://arxiv.org/abs/2210.17323) algorithm is applied for quantization, as implemented in the [llm-compressor](https://github.com/vllm-project/llm-compressor) library. + +## Deployment + +This model can be deployed efficiently using the [vLLM](https://docs.vllm.ai/en/latest/) backend, as shown in the example below. + +```python +from vllm import LLM, SamplingParams +from transformers import AutoTokenizer + +model_id = "RedHatAI/Qwen2.5-7B-quantized.w4a16" +number_gpus = 1 +max_model_len = 8192 + +sampling_params = SamplingParams(temperature=0.7, top_p=0.8, max_tokens=256) + +tokenizer = AutoTokenizer.from_pretrained(model_id) + +prompt = "Give me a short introduction to large language model." + +llm = LLM(model=model_id, tensor_parallel_size=number_gpus, max_model_len=max_model_len) + +outputs = llm.generate(prompt, sampling_params) + +generated_text = outputs[0].outputs[0].text +print(generated_text) +``` + +vLLM aslo supports OpenAI-compatible serving. See the [documentation](https://docs.vllm.ai/en/latest/) for more details. + +## Creation + +
+ Creation details + This model was created with [llm-compressor](https://github.com/vllm-project/llm-compressor) by running the code snippet below. + + + ```python + from transformers import AutoModelForCausalLM, AutoTokenizer + from llmcompressor.modifiers.quantization import GPTQModifier + from llmcompressor.transformers import oneshot + from datasets import load_dataset + + # Load model + model_stub = "Qwen/Qwen2.5-7B" + model_name = model_stub.split("/")[-1] + + num_samples = 3072 + max_seq_len = 8192 + + tokenizer = AutoTokenizer.from_pretrained(model_stub) + + model = AutoModelForCausalLM.from_pretrained( + model_stub, + device_map="auto", + torch_dtype="auto", + ) + + def preprocess_fn(example): + return {"text": tokenizer.apply_chat_template(example["messages"], add_generation_prompt=False, tokenize=False)} + + ds = load_dataset("neuralmagic/LLM_compression_calibration", split="train") + ds = ds.map(preprocess_fn) + + # Configure the quantization algorithm and scheme + recipe = GPTQModifier( + targets="Linear", + scheme="W4A16", + ignore=["lm_head"], + sequential_targets=["Qwen2DecoderLayer"], + dampening_frac=0.1, + ) + + # Apply quantization + oneshot( + model=model, + dataset=ds, + recipe=recipe, + max_seq_length=max_seq_len, + num_calibration_samples=num_samples, + ) + + # Save to disk in compressed-tensors format + save_path = model_name + "-quantized.w4a16" + model.save_pretrained(save_path) + tokenizer.save_pretrained(save_path) + print(f"Model and tokenizer saved to: {save_path}") + ``` +
+ +## Evaluation + +The model was evaluated on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) leaderboard tasks (version 1) with the [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/387Bbd54bc621086e05aa1b030d8d4d5635b25e6) (commit 387Bbd54bc621086e05aa1b030d8d4d5635b25e6) and the [vLLM](https://docs.vllm.ai/en/stable/) engine, using the following command: +``` +lm_eval \ + --model vllm \ + --model_args pretrained="neuralmagic/Qwen2.5-7B-quantized.w4a16",dtype=auto,gpu_memory_utilization=0.9,add_bos_token=True,max_model_len=4096,enable_chunk_prefill=True,tensor_parallel_size=1 \ + --tasks openllm \ + --batch_size auto +``` + +### Accuracy + +#### Open LLM Leaderboard evaluation scores + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Benchmark + Qwen2.5-7B + Qwen2.5-7B-quantized.w4a16
(this model) + 		Recovery +
MMLU (5-shot) + 74.15 + 73.47 + 99.1% +
ARC Challenge (25-shot) + 59.39 + 58.70 + 98.9% +
GSM-8K (5-shot, strict-match) + 79.76 + 79.08 + 99.1% +
Hellaswag (10-shot) + 80.17 + 79.39 + 99.0% +
Winogrande (5-shot) + 75.69 + 76.01 + 100.4% +
TruthfulQA (0-shot, mc2) + 56.38 + 55.48 + 98.4% +
Average + 70.92 + 70.35 + 99.2% +
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