Instructions to use Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression") model = AutoModelForSequenceClassification.from_pretrained("Mantis-VL/mantis-8b-idefics2-classification-example_4096_regression") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_convert_rgb": true, | |
| "do_image_splitting": false, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Idefics2ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "Idefics2Processor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 980, | |
| "shortest_edge": 378 | |
| } | |
| } | |