--- base_model: Qwen/Qwen2.5-0.5B tags: - gguf - llama.cpp - quantized - trl - sft --- # qwen-capybara-medium-gguf This is a GGUF conversion of [evalstate/qwen-capybara-medium](https://huggingface.co/evalstate/qwen-capybara-medium), which is a LoRA fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B). ## Model Details - **Base Model:** Qwen/Qwen2.5-0.5B - **Fine-tuned Model:** evalstate/qwen-capybara-medium - **Training:** Supervised Fine-Tuning (SFT) with TRL - **Format:** GGUF (for llama.cpp, Ollama, LM Studio, etc.) ## Available Quantizations | File | Quant | Size | Description | Use Case | |------|-------|------|-------------|----------| | qwen-capybara-medium-f16.gguf | F16 | ~1GB | Full precision | Best quality, slower | | qwen-capybara-medium-q8_0.gguf | Q8_0 | ~500MB | 8-bit | High quality | | qwen-capybara-medium-q5_k_m.gguf | Q5_K_M | ~350MB | 5-bit medium | Good quality, smaller | | qwen-capybara-medium-q4_k_m.gguf | Q4_K_M | ~300MB | 4-bit medium | Recommended - good balance | ## Usage ### With llama.cpp ```bash # Download model huggingface-cli download evalstate/qwen-capybara-medium-gguf qwen-capybara-medium-q4_k_m.gguf # Run with llama.cpp ./llama-cli -m qwen-capybara-medium-q4_k_m.gguf -p "Your prompt here" ``` ### With Ollama 1. Create a `Modelfile`: ``` FROM ./qwen-capybara-medium-q4_k_m.gguf ``` 2. Create the model: ```bash ollama create qwen-capybara -f Modelfile ollama run qwen-capybara ``` ### With LM Studio 1. Download the `.gguf` file 2. Import into LM Studio 3. Start chatting! ## Training Details This model was fine-tuned using: - **Dataset:** trl-lib/Capybara (1,000 examples) - **Method:** Supervised Fine-Tuning with LoRA - **Epochs:** 3 - **LoRA rank:** 16 - **Hardware:** A10G Large GPU ## License Inherits the license from the base model: Qwen/Qwen2.5-0.5B ## Citation ```bibtex @misc{qwen-capybara-medium-gguf, author = {evalstate}, title = {Qwen Capybara Medium GGUF}, year = {2025}, publisher = {Hugging Face}, url = {https://huggingface.co/evalstate/qwen-capybara-medium-gguf} } ``` --- *Converted to GGUF format using llama.cpp*