--- license: other datasets: - tiiuae/falcon-refinedweb - bigcode/the-stack-github-issues - bigcode/commitpackft - bigcode/starcoderdata - EleutherAI/proof-pile-2 - meta-math/MetaMathQA language: - en tags: - causal-lm - code - llama-cpp - gguf-my-repo metrics: - code_eval library_name: transformers base_model: stabilityai/stable-code-3b model-index: - name: stabilityai/stable-code-3b results: - task: type: text-generation dataset: name: MultiPL-HumanEval (Python) type: nuprl/MultiPL-E metrics: - type: pass@1 value: 32.4 name: pass@1 verified: false - type: pass@1 value: 30.9 name: pass@1 verified: false - type: pass@1 value: 32.1 name: pass@1 verified: false - type: pass@1 value: 32.1 name: pass@1 verified: false - type: pass@1 value: 24.2 name: pass@1 verified: false - type: pass@1 value: 23.0 name: pass@1 verified: false --- # AIronMind/stable-code-3b-Q4_K_M-GGUF This model was converted to GGUF format from [`stabilityai/stable-code-3b`](https://huggingface.co/stabilityai/stable-code-3b) 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/stabilityai/stable-code-3b) for more details on the model. ## 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 AIronMind/stable-code-3b-Q4_K_M-GGUF --hf-file stable-code-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo AIronMind/stable-code-3b-Q4_K_M-GGUF --hf-file stable-code-3b-q4_k_m.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 AIronMind/stable-code-3b-Q4_K_M-GGUF --hf-file stable-code-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo AIronMind/stable-code-3b-Q4_K_M-GGUF --hf-file stable-code-3b-q4_k_m.gguf -c 2048 ```