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NuExtract Bpw6 EXL2 by blockblockblock

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Model Card on HF 🤗: https://huggingface.co/blockblockblock/NuExtract-bpw6-exl2 

NuExtract Bpw6 EXL2 Benchmarks

LLME Score: 0.1997
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NuExtract Bpw6 EXL2 (blockblockblock/NuExtract-bpw6-exl2)

NuExtract Bpw6 EXL2 Parameters and Internals

Model Type 
information extraction, extractive model
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
information extraction
Additional Notes 
NuExtract is purely extractive.
Supported Languages 
en (full)
Training Details 
Data Sources:
private high-quality synthetic dataset
Methodology:
fine-tuning
Context Length:
2000
Input Output 
Input Format:
JSON template
Accepted Modalities:
text
Output Format:
present in the original text
Performance Tips:
Provide example of output formatting
LLM NameNuExtract Bpw6 EXL2
Repository 🤗https://huggingface.co/blockblockblock/NuExtract-bpw6-exl2 
Required VRAM3 GB
Updated2025-02-03
Maintainerblockblockblock
Model Typephi3
Instruction-BasedYes
Model Files  3.0 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitecturePhi3ForCausalLM
Licensemit
Context Length4096
Model Max Length4096
Transformers Version4.42.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<|end-output|>
Vocabulary Size32064
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than blockblockblock/NuExtract-bpw6-exl2.

Rank the NuExtract Bpw6 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 v20241227
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