File size: 1,664 Bytes
58db0b8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
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.
|