--- pipeline_tag: text-generation base_model: bigcode/starcoder2-15b-instruct-v0.1 datasets: - bigcode/self-oss-instruct-sc2-exec-filter-50k license: bigcode-openrail-m library_name: transformers tags: - code - TensorBlock - GGUF model-index: - name: starcoder2-15b-instruct-v0.1 results: - task: type: text-generation dataset: name: LiveCodeBench (code generation) type: livecodebench-codegeneration metrics: - type: pass@1 value: 20.4 - task: type: text-generation dataset: name: LiveCodeBench (self repair) type: livecodebench-selfrepair metrics: - type: pass@1 value: 20.9 - task: type: text-generation dataset: name: LiveCodeBench (test output prediction) type: livecodebench-testoutputprediction metrics: - type: pass@1 value: 29.8 - task: type: text-generation dataset: name: LiveCodeBench (code execution) type: livecodebench-codeexecution metrics: - type: pass@1 value: 28.1 - task: type: text-generation dataset: name: HumanEval type: humaneval metrics: - type: pass@1 value: 72.6 - task: type: text-generation dataset: name: HumanEval+ type: humanevalplus metrics: - type: pass@1 value: 63.4 - task: type: text-generation dataset: name: MBPP type: mbpp metrics: - type: pass@1 value: 75.2 - task: type: text-generation dataset: name: MBPP+ type: mbppplus metrics: - type: pass@1 value: 61.2 - task: type: text-generation dataset: name: DS-1000 type: ds-1000 metrics: - type: pass@1 value: 40.6 ---
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## bigcode/starcoder2-15b-instruct-v0.1 - GGUF This repo contains GGUF format model files for [bigcode/starcoder2-15b-instruct-v0.1](https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` <|endoftext|>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions. ### Instruction {prompt} ### Response ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [starcoder2-15b-instruct-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q2_K.gguf) | Q2_K | 5.768 GB | smallest, significant quality loss - not recommended for most purposes | | [starcoder2-15b-instruct-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q3_K_S.gguf) | Q3_K_S | 6.507 GB | very small, high quality loss | | [starcoder2-15b-instruct-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q3_K_M.gguf) | Q3_K_M | 7.492 GB | very small, high quality loss | | [starcoder2-15b-instruct-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q3_K_L.gguf) | Q3_K_L | 8.350 GB | small, substantial quality loss | | [starcoder2-15b-instruct-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q4_0.gguf) | Q4_0 | 8.443 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [starcoder2-15b-instruct-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q4_K_S.gguf) | Q4_K_S | 8.532 GB | small, greater quality loss | | [starcoder2-15b-instruct-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q4_K_M.gguf) | Q4_K_M | 9.183 GB | medium, balanced quality - recommended | | [starcoder2-15b-instruct-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q5_0.gguf) | Q5_0 | 10.265 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [starcoder2-15b-instruct-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q5_K_S.gguf) | Q5_K_S | 10.265 GB | large, low quality loss - recommended | | [starcoder2-15b-instruct-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q5_K_M.gguf) | Q5_K_M | 10.646 GB | large, very low quality loss - recommended | | [starcoder2-15b-instruct-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q6_K.gguf) | Q6_K | 12.201 GB | very large, extremely low quality loss | | [starcoder2-15b-instruct-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-instruct-v0.1-GGUF/blob/main/starcoder2-15b-instruct-v0.1-Q8_0.gguf) | Q8_0 | 15.800 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/starcoder2-15b-instruct-v0.1-GGUF --include "starcoder2-15b-instruct-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR ``` If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: ```shell huggingface-cli download tensorblock/starcoder2-15b-instruct-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```