--- library_name: transformers base_model: nbeerbower/phi3.5-gutenberg-4B datasets: - jondurbin/gutenberg-dpo-v0.1 license: mit tags: - llama-cpp - gguf-my-repo --- # Triangle104/phi3.5-gutenberg-4B-Q4_K_S-GGUF This model was converted to GGUF format from [`nbeerbower/phi3.5-gutenberg-4B`](https://huggingface.co/nbeerbower/phi3.5-gutenberg-4B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/nbeerbower/phi3.5-gutenberg-4B) for more details on the model. --- Model details: - microsoft/Phi-3.5-mini-instruct finetuned on jondurbin/gutenberg-dpo-v0.1. Method Finetuned using 2x RTX 4060 Ti for 3 epochs. Fine-tune Llama 3 with ORPO --- ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/phi3.5-gutenberg-4B-Q4_K_S-GGUF --hf-file phi3.5-gutenberg-4b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/phi3.5-gutenberg-4B-Q4_K_S-GGUF --hf-file phi3.5-gutenberg-4b-q4_k_s.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Triangle104/phi3.5-gutenberg-4B-Q4_K_S-GGUF --hf-file phi3.5-gutenberg-4b-q4_k_s.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/phi3.5-gutenberg-4B-Q4_K_S-GGUF --hf-file phi3.5-gutenberg-4b-q4_k_s.gguf -c 2048 ```