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:
- 64eee5f07c91fc15b93c0c69d37834b10f1636f3a2774baaf5a5878b9f77eb55
- Size of remote file:
- 709 MB
- SHA256:
- e75e4c723e2ff445797b48db5d19bbe92ede848837abab5f4f43917e3db2bf20
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