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Model: MaziyarPanahi/calme-3.2-baguette-3b Source: Original Platform
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README.md
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README.md
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---
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language:
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- fr
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- en
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license: other
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library_name: transformers
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tags:
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- chat
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- qwen
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- qwen2.5
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- finetune
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- french
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- english
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base_model: Qwen/Qwen2.5-3B
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datasets:
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- MaziyarPanahi/french_instruct_sharegpt
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- MaziyarPanahi/calme-legalkit-v0.2
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model_name: calme-3.2-baguette-3b
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license_name: qwen-research
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license_link: https://huggingface.co/Qwen/Qwen2.5-3B/blob/main/LICENSE
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pipeline_tag: text-generation
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inference: false
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model_creator: MaziyarPanahi
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quantized_by: MaziyarPanahi
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model-index:
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- name: calme-3.2-baguette-3b
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 63.38
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 25.87
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 3.1
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 5.93
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 8.6
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 25.98
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=MaziyarPanahi/calme-3.2-baguette-3b
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name: Open LLM Leaderboard
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---
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<img src="./calme_3.png" alt="Calme-3 Models" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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> [!TIP]
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> This is avery small model, so it might not perform well for some prompts and may be sensitive to hyper parameters. I would appreciate any feedback to see if I can fix any issues in the next iteration. ❤️
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# MaziyarPanahi/calme-3.2-baguette-3b
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This model is an advanced iteration of the powerful Qwen/Qwen2.5-3B, fine-tuned specifically to enhance its capabilities across general domains in both French and English.
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# ⚡ Quantized GGUF
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All GGUF models are available here: [MaziyarPanahi/calme-3.2-baguette-3b-GGUF](https://huggingface.co/MaziyarPanahi/calme-3.2-baguette-3b-GGUF)
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# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__calme-3.2-baguette-3b)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |22.14|
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|IFEval (0-Shot) |63.38|
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|BBH (3-Shot) |25.87|
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|MATH Lvl 5 (4-Shot)| 3.10|
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|GPQA (0-shot) | 5.93|
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|MuSR (0-shot) | 8.60|
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|MMLU-PRO (5-shot) |25.98|
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# Prompt Template
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This model uses `ChatML` prompt template:
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```
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<|im_start|>system
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{System}
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<|im_end|>
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<|im_start|>user
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{User}
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<|im_end|>
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<|im_start|>assistant
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{Assistant}
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````
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# How to use
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```python
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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messages = [
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{"role": "user", "content": "Who are you?"},
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]
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pipe = pipeline("text-generation", model="MaziyarPanahi/calme-3.2-baguette-3b")
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pipe(messages)
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# Load model directly
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-3.2-baguette-3b")
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model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-3.2-baguette-3b")
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```
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# Ethical Considerations
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As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.
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