--- license: apache-2.0 pipeline_tag: text-generation language: - fr - en tags: - openllm-france - TensorBlock - GGUF datasets: - cmh/alpaca_data_cleaned_fr_52k - OpenLLM-France/Croissant-Aligned-Instruct - Gael540/dataSet_ens_sup_fr-v1 - ai2-adapt-dev/flan_v2_converted - teknium/OpenHermes-2.5 - allenai/tulu-3-sft-personas-math - allenai/tulu-3-sft-personas-math-grade - allenai/WildChat-1M base_model: OpenLLM-France/Lucie-7B-Instruct-v1.1 widget: - text: 'Quelle est la capitale de l''Espagne ? Madrid. Quelle est la capitale de la France ?' example_title: Capital cities in French group: 1-shot Question Answering training_progress: context_length: 32000 ---
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[![Website](https://img.shields.io/badge/Website-tensorblock.co-blue?logo=google-chrome&logoColor=white)](https://tensorblock.co) [![Twitter](https://img.shields.io/twitter/follow/tensorblock_aoi?style=social)](https://twitter.com/tensorblock_aoi) [![Discord](https://img.shields.io/badge/Discord-Join%20Us-5865F2?logo=discord&logoColor=white)](https://discord.gg/Ej5NmeHFf2) [![GitHub](https://img.shields.io/badge/GitHub-TensorBlock-black?logo=github&logoColor=white)](https://github.com/TensorBlock) [![Telegram](https://img.shields.io/badge/Telegram-Group-blue?logo=telegram)](https://t.me/TensorBlock) ## OpenLLM-France/Lucie-7B-Instruct-v1.1 - GGUF This repo contains GGUF format model files for [OpenLLM-France/Lucie-7B-Instruct-v1.1](https://huggingface.co/OpenLLM-France/Lucie-7B-Instruct-v1.1). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5). ## Our projects
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## Prompt template ``` <|start_header_id|>system<|end_header_id|> {system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|> {prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|> ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [Lucie-7B-Instruct-v1.1-Q2_K.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q2_K.gguf) | Q2_K | 2.584 GB | smallest, significant quality loss - not recommended for most purposes | | [Lucie-7B-Instruct-v1.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q3_K_S.gguf) | Q3_K_S | 2.988 GB | very small, high quality loss | | [Lucie-7B-Instruct-v1.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q3_K_M.gguf) | Q3_K_M | 3.305 GB | very small, high quality loss | | [Lucie-7B-Instruct-v1.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q3_K_L.gguf) | Q3_K_L | 3.577 GB | small, substantial quality loss | | [Lucie-7B-Instruct-v1.1-Q4_0.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q4_0.gguf) | Q4_0 | 3.844 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [Lucie-7B-Instruct-v1.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q4_K_S.gguf) | Q4_K_S | 3.871 GB | small, greater quality loss | | [Lucie-7B-Instruct-v1.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q4_K_M.gguf) | Q4_K_M | 4.069 GB | medium, balanced quality - recommended | | [Lucie-7B-Instruct-v1.1-Q5_0.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q5_0.gguf) | Q5_0 | 4.649 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [Lucie-7B-Instruct-v1.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q5_K_S.gguf) | Q5_K_S | 4.649 GB | large, low quality loss - recommended | | [Lucie-7B-Instruct-v1.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q5_K_M.gguf) | Q5_K_M | 4.765 GB | large, very low quality loss - recommended | | [Lucie-7B-Instruct-v1.1-Q6_K.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q6_K.gguf) | Q6_K | 5.504 GB | very large, extremely low quality loss | | [Lucie-7B-Instruct-v1.1-Q8_0.gguf](https://huggingface.co/tensorblock/Lucie-7B-Instruct-v1.1-GGUF/blob/main/Lucie-7B-Instruct-v1.1-Q8_0.gguf) | Q8_0 | 7.128 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/Lucie-7B-Instruct-v1.1-GGUF --include "Lucie-7B-Instruct-v1.1-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/Lucie-7B-Instruct-v1.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```