--- library_name: transformers license: apache-2.0 language: - en datasets: - HuggingFaceFW/fineweb-edu tags: - TensorBlock - GGUF base_model: HuggingFaceFW/ablation-model-fineweb-edu ---
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## HuggingFaceFW/ablation-model-fineweb-edu - GGUF This repo contains GGUF format model files for [HuggingFaceFW/ablation-model-fineweb-edu](https://huggingface.co/HuggingFaceFW/ablation-model-fineweb-edu). 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 ``` ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [ablation-model-fineweb-edu-Q2_K.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q2_K.gguf) | Q2_K | 0.630 GB | smallest, significant quality loss - not recommended for most purposes | | [ablation-model-fineweb-edu-Q3_K_S.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q3_K_S.gguf) | Q3_K_S | 0.725 GB | very small, high quality loss | | [ablation-model-fineweb-edu-Q3_K_M.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q3_K_M.gguf) | Q3_K_M | 0.803 GB | very small, high quality loss | | [ablation-model-fineweb-edu-Q3_K_L.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q3_K_L.gguf) | Q3_K_L | 0.870 GB | small, substantial quality loss | | [ablation-model-fineweb-edu-Q4_0.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q4_0.gguf) | Q4_0 | 0.924 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [ablation-model-fineweb-edu-Q4_K_S.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q4_K_S.gguf) | Q4_K_S | 0.932 GB | small, greater quality loss | | [ablation-model-fineweb-edu-Q4_K_M.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q4_K_M.gguf) | Q4_K_M | 0.985 GB | medium, balanced quality - recommended | | [ablation-model-fineweb-edu-Q5_0.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q5_0.gguf) | Q5_0 | 1.112 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [ablation-model-fineweb-edu-Q5_K_S.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q5_K_S.gguf) | Q5_K_S | 1.112 GB | large, low quality loss - recommended | | [ablation-model-fineweb-edu-Q5_K_M.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q5_K_M.gguf) | Q5_K_M | 1.143 GB | large, very low quality loss - recommended | | [ablation-model-fineweb-edu-Q6_K.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q6_K.gguf) | Q6_K | 1.311 GB | very large, extremely low quality loss | | [ablation-model-fineweb-edu-Q8_0.gguf](https://huggingface.co/tensorblock/ablation-model-fineweb-edu-GGUF/blob/main/ablation-model-fineweb-edu-Q8_0.gguf) | Q8_0 | 1.698 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/ablation-model-fineweb-edu-GGUF --include "ablation-model-fineweb-edu-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/ablation-model-fineweb-edu-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```