---
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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## 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
## 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'
```