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Synatra Mixtral 8x7B by maywell

 »  All LLMs  »  maywell  »  Synatra Mixtral 8x7B   URL Share it on

  1791   
  Autotrain compatible   Conversational   En   Endpoints compatible   Ko   Mixtral   Moe   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/maywell/Synatra-Mixtral-8x7B 

Synatra Mixtral 8x7B Benchmarks

LLME Score: 0.18333
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Synatra Mixtral 8x7B (maywell/Synatra-Mixtral-8x7B)

Synatra Mixtral 8x7B Parameters and Internals

Additional Notes 
The model showcases superior comprehension and inference capabilities.
Supported Languages 
ko (unknown), en (unknown)
Training Details 
Methodology:
fine-tuned version using Korean datasets
Hardware Used:
A100 80GB * 6
Input Output 
Input Format:
Alpaca format: '### Instruction: {input} ### Response: {output}'
LLM NameSynatra Mixtral 8x7B
Repository 🤗https://huggingface.co/maywell/Synatra-Mixtral-8x7B 
Required VRAM93.6 GB
Updated2025-02-22
Maintainermaywell
Model Typemixtral
Model Files  4.9 GB: 1-of-19   5.0 GB: 2-of-19   5.0 GB: 3-of-19   4.9 GB: 4-of-19   5.0 GB: 5-of-19   5.0 GB: 6-of-19   4.9 GB: 7-of-19   5.0 GB: 8-of-19   5.0 GB: 9-of-19   4.9 GB: 10-of-19   5.0 GB: 11-of-19   5.0 GB: 12-of-19   5.0 GB: 13-of-19   4.9 GB: 14-of-19   5.0 GB: 15-of-19   5.0 GB: 16-of-19   4.9 GB: 17-of-19   5.0 GB: 18-of-19   4.2 GB: 19-of-19
Supported Languagesko en
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than maywell/Synatra-Mixtral-8x7B.

Rank the Synatra Mixtral 8x7B 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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Release v20241227
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