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Smaugv0.1 AWQ by LoneStriker

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  4-bit   Autotrain compatible   Awq Base model:mistralai/mistral-7... Base model:quantized:mistralai...   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Smaugv0.1-AWQ 

Smaugv0.1 AWQ Benchmarks

LLME Score: 0.15966
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Smaugv0.1 AWQ (LoneStriker/Smaugv0.1-AWQ)

Smaugv0.1 AWQ Parameters and Internals

LLM NameSmaugv0.1 AWQ
Repository 🤗https://huggingface.co/LoneStriker/Smaugv0.1-AWQ 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM19.3 GB
Updated2025-03-12
MaintainerLoneStriker
Model Typellama
Model Files  10.0 GB: 1-of-2   9.3 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length200000
Model Max Length200000
Transformers Version4.37.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Smaugv0.1-AWQ.

Rank the Smaugv0.1 AWQ 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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