Instructions to use microsoft/git-base-vqav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/git-base-vqav2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="microsoft/git-base-vqav2")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("microsoft/git-base-vqav2") model = AutoModelForImageTextToText.from_pretrained("microsoft/git-base-vqav2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73537d6bd59f534dcb9a2557056c0bfe40396827381322918efdcf807e418965
- Size of remote file:
- 709 MB
- SHA256:
- d6fe0c0b99e7a8018f3097e536415393f3c7023129511eb7eee6e15b41fe4f50
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