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WestLake 7B V2 GGUF by TheBloke

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Base model:quantized:senseable... Base model:senseable/westlake-...   En   Gguf   Mistral   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/WestLake-7B-v2-GGUF 

WestLake 7B V2 GGUF Benchmarks

LLME Score: 0.18085
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WestLake 7B V2 GGUF (TheBloke/WestLake-7B-v2-GGUF)

WestLake 7B V2 GGUF Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
creative writing, education, gaming, customer support, social media
Applications:
authors generating new ideas, interactive role-play scenarios, dynamic NPC interactions, chatbots, engaging content generation
Primary Use Cases:
Role-play, text generation
Additional Notes 
Westlake 7B is built upon a vast corpus enabling it to generate contextually relevant responses. It excels in role-play and text generation tasks with an impressive size of 7 billion parameters.
Supported Languages 
en (Full proficiency)
LLM NameWestLake 7B V2 GGUF
Repository 🤗https://huggingface.co/TheBloke/WestLake-7B-v2-GGUF 
Model NameWestlake 7B V2
Model CreatorCommon Sense
Base Model(s)  WestLake 7B V2   senseable/WestLake-7B-v2
Model Size7b
Required VRAM2.7 GB
Updated2025-01-03
MaintainerTheBloke
Model Typemistral
Model Files  2.7 GB   3.8 GB   3.5 GB   3.2 GB   4.1 GB   4.4 GB   4.1 GB   5.0 GB   5.1 GB   5.0 GB   5.9 GB   7.7 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseapache-2.0

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/WestLake-7B-v2-GGUF.

Rank the WestLake 7B V2 GGUF 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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Release v20241227
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