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 training_args.bin from kunal18/Vilt_Model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/kunal18/Vilt_Model/resolve/main/training_args.bin
- Command line
-
hf download hf://kunal18/Vilt_Model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kunal18/Vilt_Model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- f016b4dc9514f0c83498c704c110403ce34eed0bde4a5711616fa1aa00805fd3
- Size of remote file:
- 4.92 kB
- SHA256:
- 5985fe0f1685c68f860084b5c6822c1effc1bfb6d7bdd3c8060dc1a6d172b4a3
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