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Japanese Starling ChatV 7B EXL2 by AbeShinzo0708

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  7   
  6-bit   Autotrain compatible   Endpoints compatible   Exl2   Ja   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/AbeShinzo0708/Japanese-Starling-ChatV-7B-exl2 

Japanese Starling ChatV 7B EXL2 Benchmarks

LLME Score: 0.17999
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Japanese Starling ChatV 7B EXL2 (AbeShinzo0708/Japanese-Starling-ChatV-7B-exl2)

Japanese Starling ChatV 7B EXL2 Parameters and Internals

Model Type 
text generation, chat
Additional Notes 
6bit quantized model
Supported Languages 
ja (Japanese)
LLM NameJapanese Starling ChatV 7B EXL2
Repository 🤗https://huggingface.co/AbeShinzo0708/Japanese-Starling-ChatV-7B-exl2 
Base Model(s)  Japanese Starling ChatV 7B   TFMC/Japanese-Starling-ChatV-7B
Model Size7b
Required VRAM5.6 GB
Updated2025-02-22
MaintainerAbeShinzo0708
Model Typemistral
Model Files  5.6 GB
Supported Languagesja
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
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 AbeShinzo0708/Japanese-Starling-ChatV-7B-exl2.

Rank the Japanese Starling ChatV 7B EXL2 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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