Smaugv0.1 5.0bpw H6 EXL2 by LoneStriker

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  Merged Model   Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Conversational   Endpoints compatible   Exl2   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Smaugv0.1 5.0bpw H6 EXL2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Smaugv0.1 5.0bpw H6 EXL2 Parameters and Internals

LLM NameSmaugv0.1 5.0bpw H6 EXL2
Repository ๐Ÿค—https://huggingface.co/LoneStriker/Smaugv0.1-5.0bpw-h6-exl2 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Merged ModelYes
Model Size7b
Required VRAM22.3 GB
Updated2024-10-08
MaintainerLoneStriker
Model Typellama
Model Files  8.6 GB: 1-of-3   8.6 GB: 2-of-3   5.1 GB: 3-of-3
Quantization Typeexl2
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length200000
Model Max Length200000
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typebfloat16
Smaugv0.1 5.0bpw H6 EXL2 (LoneStriker/Smaugv0.1-5.0bpw-h6-exl2)

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Smaugv0.1-5.0bpw-h6-exl2.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803