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Mistral 7B Instruct V0.2 AWQ by Vidushee

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  4-bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors

Mistral 7B Instruct V0.2 AWQ Benchmarks

LMSys ELO: 1072 vs 1272 (so35)-15.7%
ARC: 63.14 vs 96.7 (so35)-34.7%
HellaSwag: 84.88 vs 95.3 (gpt4)-10.9%
MMLU: 60.78 vs 88.3 (so35)-31.2%
TruthfulQA: 68.26 vs 59 (gpt4)15.7%
WinoGrande: 77.19 vs 87.5 (gpt4)-11.8%
GSM8K: 40.03 vs 96.4 (so35)-58.5%
LLME Score: 0.30726
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Mistral 7B Instruct V0.2 AWQ Parameters and Internals

LLM NameMistral 7B Instruct V0.2 AWQ
Repository 🤗https://huggingface.co/Vidushee/Mistral-7B-Instruct-v0.2-awq 
Base Model(s)  jan-hq/Mistral-7B-Instruct-v0.2-SLERP   jan-hq/Mistral-7B-Instruct-v0.2-SLERP
Model Size7b
Required VRAM4.2 GB
Updated2024-10-07
MaintainerVidushee
Model Typemistral
Instruction-BasedYes
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
Mistral 7B Instruct V0.2 AWQ (Vidushee/Mistral-7B-Instruct-v0.2-awq)

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Rank the Mistral 7B Instruct V0.2 AWQ Capabilities

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