WestLake 10.7B V2 GGUF by froggeric

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  Merged Model   Autotrain compatible Base model:quantized:senseable... Base model:senseable/westlake-...   En   Endpoints compatible   Gguf   Mistral   Q4   Quantized   Region:us

WestLake 10.7B V2 GGUF Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
WestLake 10.7B V2 GGUF (froggeric/WestLake-10.7B-v2-GGUF)

WestLake 10.7B V2 GGUF Parameters and Internals

Model Type 
Role-Play, Text Generation
Use Cases 
Areas:
research, commercial applications
Applications:
Creative Writing, Education, Gaming, Customer Support, Social Media
Primary Use Cases:
Role-Play scenarios, Text Generation
Considerations:
Ensure responsible usage and avoid harmful content generation.
Additional Notes 
First viable self-merge obtained after extensive testing.
Supported Languages 
en (Proficient)
Training Details 
Methodology:
Merges various configurations of the WestLake-7B-v2 model using the passthrough merge method.
Context Length:
8192
Input Output 
Accepted Modalities:
text
Performance Tips:
Using larger context size than trained can cause problems.
LLM NameWestLake 10.7B V2 GGUF
Repository ๐Ÿค—https://huggingface.co/froggeric/WestLake-10.7B-v2-GGUF 
Base Model(s)  WestLake 7B V2   senseable/WestLake-7B-v2
Merged ModelYes
Model Size7b
Required VRAM6.1 GB
Updated2025-03-12
Maintainerfroggeric
Model Typemistral
Model Files  6.1 GB   7.4 GB   8.8 GB   11.4 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|q4
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.1
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than froggeric/WestLake-10.7B-v2-GGUF.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227