---
language:
- fr
- en
license: other
library_name: transformers
tags:
- chat
- qwen
- qwen2.5
- finetune
- french
- english
- TensorBlock
- GGUF
base_model: MaziyarPanahi/calme-3.2-baguette-3b
datasets:
- MaziyarPanahi/french_instruct_sharegpt
- MaziyarPanahi/calme-legalkit-v0.2
license_name: qwen-research
license_link: https://huggingface.co/Qwen/Qwen2.5-3B/blob/main/LICENSE
pipeline_tag: text-generation
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
model-index:
- name: calme-3.2-baguette-3b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 63.38
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 25.87
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 3.1
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 5.93
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.6
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 25.98
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
name: Open LLM Leaderboard
---
## MaziyarPanahi/calme-3.2-baguette-3b - GGUF
This repo contains GGUF format model files for [MaziyarPanahi/calme-3.2-baguette-3b](https://huggingface.co/MaziyarPanahi/calme-3.2-baguette-3b).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
## Prompt template
```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [calme-3.2-baguette-3b-Q2_K.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q2_K.gguf) | Q2_K | 1.274 GB | smallest, significant quality loss - not recommended for most purposes |
| [calme-3.2-baguette-3b-Q3_K_S.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q3_K_S.gguf) | Q3_K_S | 1.454 GB | very small, high quality loss |
| [calme-3.2-baguette-3b-Q3_K_M.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q3_K_M.gguf) | Q3_K_M | 1.590 GB | very small, high quality loss |
| [calme-3.2-baguette-3b-Q3_K_L.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q3_K_L.gguf) | Q3_K_L | 1.707 GB | small, substantial quality loss |
| [calme-3.2-baguette-3b-Q4_0.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q4_0.gguf) | Q4_0 | 1.822 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [calme-3.2-baguette-3b-Q4_K_S.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q4_K_S.gguf) | Q4_K_S | 1.834 GB | small, greater quality loss |
| [calme-3.2-baguette-3b-Q4_K_M.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q4_K_M.gguf) | Q4_K_M | 1.929 GB | medium, balanced quality - recommended |
| [calme-3.2-baguette-3b-Q5_0.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q5_0.gguf) | Q5_0 | 2.169 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [calme-3.2-baguette-3b-Q5_K_S.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q5_K_S.gguf) | Q5_K_S | 2.169 GB | large, low quality loss - recommended |
| [calme-3.2-baguette-3b-Q5_K_M.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q5_K_M.gguf) | Q5_K_M | 2.224 GB | large, very low quality loss - recommended |
| [calme-3.2-baguette-3b-Q6_K.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q6_K.gguf) | Q6_K | 2.538 GB | very large, extremely low quality loss |
| [calme-3.2-baguette-3b-Q8_0.gguf](https://huggingface.co/tensorblock/calme-3.2-baguette-3b-GGUF/blob/main/calme-3.2-baguette-3b-Q8_0.gguf) | Q8_0 | 3.285 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/calme-3.2-baguette-3b-GGUF --include "calme-3.2-baguette-3b-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/calme-3.2-baguette-3b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```