Instructions to use schubertcarvalho/vilt_finetuned_200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use schubertcarvalho/vilt_finetuned_200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="schubertcarvalho/vilt_finetuned_200")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("schubertcarvalho/vilt_finetuned_200") model = AutoModelForVisualQuestionAnswering.from_pretrained("schubertcarvalho/vilt_finetuned_200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33a1df032686e32c532cd8b7d4c1baa9bbf45e165a4cf6aad927de16fcaab294
- Size of remote file:
- 452 MB
- SHA256:
- d1b7fd586ad70fb6b45f72609397796aeb2d0d3f0f3aca548bfcce8f829a9e82
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