Florence 2 Base Ft by microsoft

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  Arxiv:2311.06242   Autotrain compatible   Custom code   Florence2   Image-text-to-text   Pytorch   Region:us   Vision

Florence 2 Base Ft Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Florence 2 Base Ft (microsoft/Florence-2-base-ft)

Florence 2 Base Ft Parameters and Internals

Model Type 
vision, vision-language
Use Cases 
Areas:
Research, Commercial applications
Applications:
Image captioning, Object detection, Segmentation
Training Details 
Data Sources:
FLD-5B
Data Volume:
5.4 billion annotations across 126 million images
Methodology:
Sequence-to-sequence architecture for multi-task learning
Model Architecture:
Sequence-to-sequence architecture
Input Output 
Input Format:
Text prompts
Accepted Modalities:
text, image
Output Format:
Parsed task results
LLM NameFlorence 2 Base Ft
Repository ๐Ÿค—https://huggingface.co/microsoft/Florence-2-base-ft 
Required VRAM0.5 GB
Updated2025-01-24
Maintainermicrosoft
Model Typeflorence2
Model Files  0.5 GB
Model ArchitectureFlorence2ForConditionalGeneration
Licensemit
Model Max Length1024
Transformers Version4.41.0.dev0
Vocabulary Size51289
Torch Data Typefloat16

Best Alternatives to Florence 2 Base Ft

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Florence 2 Large Ft0K / 1.5 GB57431314
Note: green Score (e.g. "73.2") means that the model is better than microsoft/Florence-2-base-ft.

Rank the Florence 2 Base Ft 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