Instructions to use Atul8827/vilt_finetuned_200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atul8827/vilt_finetuned_200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Atul8827/vilt_finetuned_200")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Atul8827/vilt_finetuned_200") model = AutoModelForVisualQuestionAnswering.from_pretrained("Atul8827/vilt_finetuned_200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1f74de259f0ee0f5a8db02cab5a87322e42c20bb1192c2881c2fbb250c80b29
- Size of remote file:
- 4.79 kB
- SHA256:
- 06de3b2d935469e8667bc44de3d744c4a235434c5c4d6eff2926cf2885368959
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.