Instructions to use microsoft/git-large-vqav2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/git-large-vqav2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="microsoft/git-large-vqav2")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("microsoft/git-large-vqav2") model = AutoModelForMultimodalLM.from_pretrained("microsoft/git-large-vqav2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7100383f9a0df5b5c8c5be4aa1ebfeedd19b483986fd54847a459fec326f1b7f
- Size of remote file:
- 1.58 GB
- SHA256:
- 90bd4fe168bb8de07b5a75f02af6c4d4c8eaa8f39bca4fe7ccfdaeb972953c59
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