--- license: apache-2.0 datasets: - hyokwan/famili language: - ko metrics: - accuracy library_name: transformers pipeline_tag: text-generation tags: - finance - TensorBlock - GGUF base_model: hyokwan/familidata ---
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## hyokwan/familidata - GGUF This repo contains GGUF format model files for [hyokwan/familidata](https://huggingface.co/hyokwan/familidata). 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 ``` ### System: {system_prompt} ### User: {prompt} ### Assistant: ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [familidata-Q2_K.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q2_K.gguf) | Q2_K | 4.003 GB | smallest, significant quality loss - not recommended for most purposes | | [familidata-Q3_K_S.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q3_K_S.gguf) | Q3_K_S | 4.665 GB | very small, high quality loss | | [familidata-Q3_K_M.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q3_K_M.gguf) | Q3_K_M | 5.196 GB | very small, high quality loss | | [familidata-Q3_K_L.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q3_K_L.gguf) | Q3_K_L | 5.651 GB | small, substantial quality loss | | [familidata-Q4_0.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q4_0.gguf) | Q4_0 | 6.072 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [familidata-Q4_K_S.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q4_K_S.gguf) | Q4_K_S | 6.119 GB | small, greater quality loss | | [familidata-Q4_K_M.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q4_K_M.gguf) | Q4_K_M | 6.462 GB | medium, balanced quality - recommended | | [familidata-Q5_0.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q5_0.gguf) | Q5_0 | 7.397 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [familidata-Q5_K_S.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q5_K_S.gguf) | Q5_K_S | 7.397 GB | large, low quality loss - recommended | | [familidata-Q5_K_M.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q5_K_M.gguf) | Q5_K_M | 7.598 GB | large, very low quality loss - recommended | | [familidata-Q6_K.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q6_K.gguf) | Q6_K | 8.805 GB | very large, extremely low quality loss | | [familidata-Q8_0.gguf](https://huggingface.co/tensorblock/familidata-GGUF/blob/main/familidata-Q8_0.gguf) | Q8_0 | 11.404 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/familidata-GGUF --include "familidata-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/familidata-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```