---
language:
- en
license: apache-2.0
tags:
- qwen2.5
- fine-tuned
- lora
- chemistry
base_model: Qwen/Qwen2.5-14B-Instruct
---

# qwen-quantum

This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) 
using LoRA (Low-Rank Adaptation) on a chemistry dataset.

## Model Description

Fine-tuned Qwen2.5-14B model for chemistry domain tasks.

## Available Formats

- **GGUF**: `qwen_quantum_merged-q4_k_m.gguf` - Quantized for efficient inference with llama.cpp

## Usage

### Using GGUF (with llama.cpp, Ollama, LM Studio, etc.)

```bash
# Download the GGUF file
huggingface-cli download Kylan12/qwen-quantum qwen_quantum_merged-q4_k_m.gguf

# Use with llama.cpp
./llama.cpp/build/bin/llama-cli -m qwen_quantum_merged-q4_k_m.gguf -p "Your prompt here"
```

### Using HuggingFace Transformers

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Kylan12/qwen-quantum")
tokenizer = AutoTokenizer.from_pretrained("Kylan12/qwen-quantum")

prompt = "What is the IUPAC name for..."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
print(tokenizer.decode(outputs[0]))
```

## Training Details

- **Base Model**: Qwen/Qwen2.5-14B-Instruct
- **Training Method**: LoRA (Low-Rank Adaptation)
- **Dataset**: camel-ai/chemistry
- **LoRA Rank**: 16
- **LoRA Alpha**: 16
- **Target Modules**: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj

## Limitations

This model inherits the limitations of the base Qwen2.5-14B-Instruct model and may have 
additional domain-specific limitations due to the fine-tuning dataset.

## Citation

If you use this model, please cite:

```bibtex
@misc{qwen_quantum,
  author = {Your Name},
  title = {qwen-quantum},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/Kylan12/qwen-quantum}
}
```

## License

This model is released under the Apache 2.0 license, consistent with the base Qwen model.