README.md

metadata

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

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

MaziyarPanahi/calme-3.2-baguette-3b - GGUF

This repo contains GGUF format model files for MaziyarPanahi/calme-3.2-baguette-3b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Run them on the TensorBlock client using your local machine ↗

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	Q2_K	1.274 GB	smallest, significant quality loss - not recommended for most purposes
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	Q3_K_M	1.590 GB	very small, high quality loss
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	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	Q4_K_S	1.834 GB	small, greater quality loss
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	Q5_0	2.169 GB	legacy; medium, balanced quality - prefer using Q4_K_M
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	Q5_K_M	2.224 GB	large, very low quality loss - recommended
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	Q8_0	3.285 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

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:

huggingface-cli download tensorblock/calme-3.2-baguette-3b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'