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---

license: mit
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
base_model:
- Qwen/Qwen2.5-3B-Instruct
pipeline_tag: question-answering
---

# Qwen AI Research QA Model (Q4_K_M GGUF)

## Model Overview
The **Qwen AI Research QA Model** is designed for answering research-oriented AI questions with a focus on precision and depth. This model is optimized in the `Q4_K_M` format for efficient inference while maintaining high-quality responses.

## How to Use
To use this model with `llama-cpp-python`, follow these steps:

### Installation
Make sure you have `llama-cpp-python` installed:
```bash

pip install llama-cpp-python

```

### Loading the Model
```python

from llama_cpp import Llama



llm = Llama.from_pretrained(

    repo_id="InduwaraR/qwen-ai-research-qa-q4_k_m.gguf",

    filename="qwen-ai-research-qa-q4_k_m.gguf",

)

```

### Generating a Response
```python

response = llm.create_chat_completion(

    messages=[

        {"role": "user", "content": "What are the latest advancements in AI research?"}

    ]

)

print(response)

```

## Model Details
- **Model Name**: Qwen AI Research QA
- **Format**: GGUF (Q4_K_M Quantization)
- **Primary Use Case**: AI research question answering
- **Inference Framework**: `llama-cpp-python`
- **Optimized for**: Running on local hardware with reduced memory usage

## License
This model is open-source and available under the **MIT License**.

## Acknowledgments
This model is hosted by **InduwaraR** on Hugging Face. Special thanks to the **Qwen AI team** for their contributions to AI research and development.