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Youri 2x7b Dev by HachiML

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  Autotrain compatible   Endpoints compatible   Ja   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/HachiML/youri-2x7b_dev 

Youri 2x7b Dev Benchmarks

LLME Score: 0.13182
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Youri 2x7b Dev (HachiML/youri-2x7b_dev)
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Youri 2x7b Dev Parameters and Internals

Model Type 
Mixture of Experts (MoE)
Use Cases 
Areas:
natural language processing tasks
Considerations:
The model's performance in specific tasks may vary based on the benchmarks it excels in, guiding effective use.
Supported Languages 
Japanese (proficient)
Input Output 
Accepted Modalities:
text
Performance Tips:
Use the merged model for tasks where both chat and instruction following are critical.
LLM NameYouri 2x7b Dev
Repository 🤗https://huggingface.co/HachiML/youri-2x7b_dev 
Model Size11.1b
Required VRAM22.1 GB
Updated2025-09-20
MaintainerHachiML
Model Typemixtral
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   2.1 GB: 3-of-3
Supported Languagesja
Model ArchitectureMixtralForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typebfloat16

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Youri 2x7b V0.24K / 22.1 GB51
Medtulu 2x7b2K / 22.1 GB16372
Note: green Score (e.g. "73.2") means that the model is better than HachiML/youri-2x7b_dev.

Rank the Youri 2x7b Dev 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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