Instructions to use phonghoccode/vilt-finetuned-cocoqa-augmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phonghoccode/vilt-finetuned-cocoqa-augmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="phonghoccode/vilt-finetuned-cocoqa-augmentation")# Load model directly from transformers import AutoProcessor, AutoModelForQuestionAnswering processor = AutoProcessor.from_pretrained("phonghoccode/vilt-finetuned-cocoqa-augmentation") model = AutoModelForQuestionAnswering.from_pretrained("phonghoccode/vilt-finetuned-cocoqa-augmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f5813c198160430cd086f7af81077cebd1eaf928c4257275e2db43929d72d6f
- Size of remote file:
- 454 MB
- SHA256:
- 8cde645c47474e3906a055de6c45fcf7a4c834f993dd49cd92772bef7c9b6dc3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.