Instructions to use VladGK/ViLT_Binary_Classifier_Abstract_Scenes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VladGK/ViLT_Binary_Classifier_Abstract_Scenes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="VladGK/ViLT_Binary_Classifier_Abstract_Scenes")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("VladGK/ViLT_Binary_Classifier_Abstract_Scenes") model = AutoModelForVisualQuestionAnswering.from_pretrained("VladGK/ViLT_Binary_Classifier_Abstract_Scenes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ff78acc9784c8578dd6d61d42aed6c816e3276b1d5e6e3c60b9c92d64d6d879
- Size of remote file:
- 458 MB
- SHA256:
- fbb0bde3705cd2c25267816689a5809917b47815e4fc2f08fc628df9f97651bf
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