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ScikitLLM Model EXL2 by probabl-ai

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  3-bit   Autotrain compatible   Conversational   Endpoints compatible   Exl2   Mistral   Quantized   Region:us   Safetensors

ScikitLLM Model EXL2 Benchmarks

LLME Score: 0.20733
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

ScikitLLM Model EXL2 Parameters and Internals

LLM NameScikitLLM Model EXL2
Repository 🤗https://huggingface.co/probabl-ai/ScikitLLM-Model-exl2 
Required VRAM3 GB
Updated2024-09-07
Maintainerprobabl-ai
Model Typemistral
Model Files  3.0 GB
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<|im_end|>
Vocabulary Size32002
Torch Data Typebfloat16
ScikitLLM Model EXL2 (probabl-ai/ScikitLLM-Model-exl2)

Best Alternatives to ScikitLLM Model EXL2

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NemoMix Unleashed EXL2 4bpw1000K / 7.3 GB603
...cr To Json V1 HQQ 1bit Smashed32K / 1.6 GB50
...cr To Json V1 HQQ 4bit Smashed32K / 4.2 GB50
Chargen V2 8bpw EXL232K / 7.4 GB91
...tral PairRM DPO 8.0bpw H8 EXL232K / 7.4 GB32
HamSter 0.2 8.0bpw H8 EXL232K / 7.4 GB91
...N L1 Chat RL V1.3.0bpw H6 EXL232K / 3 GB300
...N L1 Chat RL V1.6.0bpw H6 EXL232K / 5.6 GB111
...Bruins V2.1.1 8.0bpw H8 EXL2 232K / 7.4 GB132
...Bruins V2.1.1 6.0bpw H6 EXL2 232K / 5.6 GB141
Note: green Score (e.g. "73.2") means that the model is better than probabl-ai/ScikitLLM-Model-exl2.

Rank the ScikitLLM Model EXL2 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 v2024072803
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