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Zebrafish 7B by mlabonne

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Zebrafish 7B is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: cc-by-nc-4.0, Merged, HF Score: 76.6, LLM Explorer Score: 0.13, Arc: 73.1, HellaSwag: 89.1, MMLU: 64.4, TruthfulQA: 77.9, WinoGrande: 84.9, GSM8K: 69.9.

  Merged Model   Arxiv:2403.19522 Base model:finetune:liminerity...   Base model:liminerity/m7-7b   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mlabonne/Zebrafish-7B 

Zebrafish 7B Benchmarks

ARC: 73.12 vs 96.7 (so35)-24.4%
HellaSwag: 89.13 vs 95.3 (gpt4)-6.5%
MMLU: 64.36 vs 88.3 (so35)-27.1%
TruthfulQA: 77.92 vs 59 (gpt4)32.1%
WinoGrande: 84.93 vs 87.5 (gpt4)-2.9%
GSM8K: 69.9 vs 96.4 (so35)-27.5%
LLME Score: 0.13227
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Zebrafish 7B (mlabonne/Zebrafish-7B)
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Zebrafish 7B Parameters and Internals

Model Type 
merge
Input Output 
Input Format:
Chat-style prompt messages structured for tokenization and generation.
Accepted Modalities:
text
Output Format:
Generated text based on input prompt.
LLM NameZebrafish 7B
Repository 🤗https://huggingface.co/mlabonne/Zebrafish-7B 
Base Model(s)  M7 7B   Experiment26 Truthy Iter 0   liminerity/M7-7b   rwitz/experiment26-truthy-iter-0
Merged ModelYes
Model Size7b
Required VRAM14.5 GB
Updated2026-04-23
Maintainermlabonne
Model Typemistral
Model Files  9.8 GB: 1-of-2   4.7 GB: 2-of-2
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than mlabonne/Zebrafish-7B.

Rank the Zebrafish 7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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