# Download the GGUF file
huggingface-cli download Kylan12/qwen-chemistry qwen_chemistry_merged-q4_k_m.gguf

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

Using HuggingFace Transformers

python

from transformers import AutoModelForCausalLM, AutoTokenizer

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

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_chemistry,
  author = {Your Name},
  title = {qwen-chemistry},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/Kylan12/qwen-chemistry}
}

License

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