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
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license: apache-2.0
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datasets:
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- TIGER-Lab/
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language:
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- en
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metrics:
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- accuracy
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library_name: transformers
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pipeline_tag: visual-question-answering
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license: apache-2.0
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datasets:
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- TIGER-Lab/VideoFeedback
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language:
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- en
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metrics:
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- accuracy/spcc
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library_name: transformers
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pipeline_tag: visual-question-answering
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