Instructions to use kunal18/Vilt_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunal18/Vilt_Model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="kunal18/Vilt_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("kunal18/Vilt_Model") model = AutoModelForVisualQuestionAnswering.from_pretrained("kunal18/Vilt_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kunal18/Vilt_Model: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
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https://huggingface.co/kunal18/Vilt_Model/resolve/main/tokenizer.json
- Command line
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hf download hf://kunal18/Vilt_Model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/kunal18/Vilt_Model/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.