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Chocolatine 3B Instruct DPO Revised by jpacifico

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  Autotrain compatible   Chocolatine   Conversational   Custom code Dataset:jpacifico/french-orca-...   En   Endpoints compatible   Fr   French   Instruct   Phi3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/jpacifico/Chocolatine-3B-Instruct-DPO-Revised 

Chocolatine 3B Instruct DPO Revised Benchmarks

MMLU Pro: 33.21
GPQA: 9.62
MUSR: 15.1
BBH: 37.16
IFEval: 56.23 vs 88 (so35)-36.1%
MATH Lvl 5: 18.05
LLME Score: 0.25035
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Chocolatine 3B Instruct DPO Revised (jpacifico/Chocolatine-3B-Instruct-DPO-Revised)
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Chocolatine 3B Instruct DPO Revised Parameters and Internals

Model Type 
LLM
Use Cases 
Areas:
Research, Commercial applications
Limitations:
No moderation mechanism
Additional Notes 
Chocolatine is a demonstration that a base model can be easily fine-tuned to achieve compelling performance.
Supported Languages 
French (High), English (High)
Training Details 
Data Sources:
jpacifico/french-orca-dpo-pairs-revised
Methodology:
DPO fine-tuning
Context Length:
4000
Input Output 
Accepted Modalities:
Text
Output Format:
Text
Release Notes 
Version:
1.2
Notes:
Larger version Chocolatine-14B available.
LLM NameChocolatine 3B Instruct DPO Revised
Repository 🤗https://huggingface.co/jpacifico/Chocolatine-3B-Instruct-DPO-Revised 
Model Size3b
Required VRAM7.7 GB
Updated2025-09-23
Maintainerjpacifico
Model Typephi3
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.7 GB: 2-of-2
Supported Languagesfr en
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length4096
Model Max Length4096
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<|endoftext|>
Vocabulary Size32064
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than jpacifico/Chocolatine-3B-Instruct-DPO-Revised.

Rank the Chocolatine 3B Instruct DPO Revised Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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