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[doc] update wrong model id #17287

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Apr 28, 2025
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[doc] update wrong model id #17287

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8 changes: 5 additions & 3 deletions docs/source/features/quantization/gptqmodel.md
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ model.save(quant_path)
To run an GPTQModel quantized model with vLLM, you can use [DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2](https://huggingface.co/ModelCloud/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2) with the following command:

```console
python examples/offline_inference/llm_engine_example.py --model DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2
python examples/offline_inference/llm_engine_example.py --model ModelCloud/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2
```

## Using GPTQModel with vLLM's Python API
Expand All @@ -80,15 +80,17 @@ prompts = [
sampling_params = SamplingParams(temperature=0.6, top_p=0.9)

# Create an LLM.
llm = LLM(model="DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2")
llm = LLM(model="ModelCloud/DeepSeek-R1-Distill-Qwen-7B-gptqmodel-4bit-vortex-v2")

# Generate texts from the prompts. The output is a list of RequestOutput objects
# that contain the prompt, generated text, and other information.
outputs = llm.generate(prompts, sampling_params)

# Print the outputs.
print("-"*50)
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
print(f"Prompt: {prompt!r}\nGenerated text: {generated_text!r}")
print("-"*50)
```