Visual Question Answering
Transformers
Safetensors
English
idefics2
text-classification
text-generation-inference
Instructions to use TIGER-Lab/VideoScore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/VideoScore with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="TIGER-Lab/VideoScore")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("TIGER-Lab/VideoScore") model = AutoModelForSequenceClassification.from_pretrained("TIGER-Lab/VideoScore") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Introduction
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- MantisScore is a video quality evaluation model, trained on VideoEval[VideoEval](https://huggingface.co/datasets/TIGER-Lab/VideoEval),
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a large video evaluation dataset with multi-aspect human scores.
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- MantisScore trained on
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