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
- Xet hash:
- 1e090c2d2774ea7875da72d682c12600bd69085e9c28674b917a49fe82ccffe2
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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