WestLake 7B V2 AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:quantized:senseable... Base model:senseable/westlake-...   En   Mistral   Quantized   Region:us   Safetensors

WestLake 7B V2 AWQ Benchmarks

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 AWQ (TheBloke/WestLake-7B-v2-AWQ)

WestLake 7B V2 AWQ Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
Creative Writing, Education, Gaming, Customer Support, Social Media
Applications:
Assisting authors, Interactive role-play scenarios in education, NPC interactions in games, Chatbots for customer support, Generating social media content
Additional Notes 
AWQ quantized model for efficient, accurate, and fast inference. Original model by Common Sense, quantized by TheBloke.
Supported Languages 
en (fluent)
Input Output 
Input Format:
{prompt}
Accepted Modalities:
text
Release Notes 
Version:
2
Notes:
Trained 1 additional epoch cycle for 3 total
LLM NameWestLake 7B V2 AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/WestLake-7B-v2-AWQ 
Model NameWestlake 7B V2
Model CreatorCommon Sense
Base Model(s)  WestLake 7B V2   senseable/WestLake-7B-v2
Model Size7b
Required VRAM4.2 GB
Updated2025-02-05
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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

Rank the WestLake 7B V2 AWQ Capabilities

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227