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Mistral Nemo Instruct 2407 EXL2 8bpw H8 by DrNicefellow

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  8-bit   Autotrain compatible   Conversational   Endpoints compatible   Exl2   Instruct   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DrNicefellow/Mistral-Nemo-Instruct-2407-exl2-8bpw-h8 

Mistral Nemo Instruct 2407 EXL2 8bpw H8 Benchmarks

LLME Score: 0.21534
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Nemo Instruct 2407 EXL2 8bpw H8 (DrNicefellow/Mistral-Nemo-Instruct-2407-exl2-8bpw-h8)

Mistral Nemo Instruct 2407 EXL2 8bpw H8 Parameters and Internals

LLM NameMistral Nemo Instruct 2407 EXL2 8bpw H8
Repository 🤗https://huggingface.co/DrNicefellow/Mistral-Nemo-Instruct-2407-exl2-8bpw-h8 
Required VRAM12.6 GB
Updated2024-12-21
MaintainerDrNicefellow
Instruction-BasedYes
Model Files  8.6 GB: 1-of-2   4.0 GB: 2-of-2
Quantization Typeexl2
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size131072

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Note: green Score (e.g. "73.2") means that the model is better than DrNicefellow/Mistral-Nemo-Instruct-2407-exl2-8bpw-h8.

Rank the Mistral Nemo Instruct 2407 EXL2 8bpw H8 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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