Instructions to use tanish1403/vilt_finetuned_200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanish1403/vilt_finetuned_200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="tanish1403/vilt_finetuned_200")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("tanish1403/vilt_finetuned_200") model = AutoModelForVisualQuestionAnswering.from_pretrained("tanish1403/vilt_finetuned_200") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "ViltFeatureExtractor", | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViltImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "ViltProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 384 | |
| }, | |
| "size_divisor": 32 | |
| } | |