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:
- f1b907f0e79cec162a1e3096cc82c57bec212138fd55ae0895e820d248e0afb4
- Size of remote file:
- 6.52 kB
- SHA256:
- 5856da871c5b5a8cdef9276b7f3b2c4c0ff835f744145bb1e20599063cf2f53f
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