--- license: bigscience-bloom-rail-1.0 language: - ak - ar - as - bm - bn - ca - code - en - es - eu - fon - fr - gu - hi - id - ig - ki - kn - lg - ln - ml - mr - ne - nso - ny - or - pa - pt - rn - rw - sn - st - sw - ta - te - tn - ts - tum - tw - ur - vi - wo - xh - yo - zh - zhs - zht - zu pipeline_tag: text-generation base_model: bigscience/bloom-1b7 tags: - TensorBlock - GGUF ---
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## bigscience/bloom-1b7 - GGUF This repo contains GGUF format model files for [bigscience/bloom-1b7](https://huggingface.co/bigscience/bloom-1b7). 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). ## Prompt template ``` ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [bloom-1b7-Q2_K.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q2_K.gguf) | Q2_K | 0.980 GB | smallest, significant quality loss - not recommended for most purposes | | [bloom-1b7-Q3_K_S.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q3_K_S.gguf) | Q3_K_S | 1.096 GB | very small, high quality loss | | [bloom-1b7-Q3_K_M.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q3_K_M.gguf) | Q3_K_M | 1.197 GB | very small, high quality loss | | [bloom-1b7-Q3_K_L.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q3_K_L.gguf) | Q3_K_L | 1.254 GB | small, substantial quality loss | | [bloom-1b7-Q4_0.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q4_0.gguf) | Q4_0 | 1.309 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [bloom-1b7-Q4_K_S.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q4_K_S.gguf) | Q4_K_S | 1.315 GB | small, greater quality loss | | [bloom-1b7-Q4_K_M.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q4_K_M.gguf) | Q4_K_M | 1.392 GB | medium, balanced quality - recommended | | [bloom-1b7-Q5_0.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q5_0.gguf) | Q5_0 | 1.509 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [bloom-1b7-Q5_K_S.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q5_K_S.gguf) | Q5_K_S | 1.509 GB | large, low quality loss - recommended | | [bloom-1b7-Q5_K_M.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q5_K_M.gguf) | Q5_K_M | 1.571 GB | large, very low quality loss - recommended | | [bloom-1b7-Q6_K.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q6_K.gguf) | Q6_K | 1.722 GB | very large, extremely low quality loss | | [bloom-1b7-Q8_0.gguf](https://huggingface.co/tensorblock/bloom-1b7-GGUF/tree/main/bloom-1b7-Q8_0.gguf) | Q8_0 | 2.226 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/bloom-1b7-GGUF --include "bloom-1b7-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/bloom-1b7-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```