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Git Base Vatex by microsoft

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  3053   
  Arxiv:2205.14100   Autotrain compatible   En   Git   Pytorch   Region:us   Safetensors   Vision
Model Card on HF 🤗: https://huggingface.co/microsoft/git-base-vatex 

Git Base Vatex Benchmarks

LLME Score: 0.08832
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Git Base Vatex (microsoft/git-base-vatex)

Git Base Vatex Parameters and Internals

Model Type 
Transformer decoder
Use Cases 
Areas:
vision, language
Applications:
image captioning, video captioning, visual question answering (VQA) on images and videos, image classification
Primary Use Cases:
video captioning
Additional Notes 
The model is fine-tuned on VATEX and is a base-sized variant of the original GIT model.
Training Details 
Data Sources:
COCO, Conceptual Captions (CC3M), SBU, Visual Genome (VG), Conceptual Captions (CC12M), ALT200M, additional 0.6B data following Hu et al. (2021a), VATEX
Data Volume:
10 million image-text pairs
Methodology:
Teacher forcing
Model Architecture:
Transformer decoder conditioned on CLIP image tokens and text tokens
LLM NameGit Base Vatex
Repository 🤗https://huggingface.co/microsoft/git-base-vatex 
Model Namemicrosoft/git-base-vatex
Model Size176.6m
Required VRAM0.7 GB
Updated2024-10-31
Maintainermicrosoft
Model Typegit
Model Files  0.7 GB   0.7 GB
Supported Languagesen
Model ArchitectureGitForCausalLM
Licensemit
Context Length1024
Model Max Length1024
Tokenizer ClassBertTokenizer
Padding Token[PAD]
Vocabulary Size30522
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than microsoft/git-base-vatex.

Rank the Git Base Vatex Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Text Generation  
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Release v20241227
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