Instructions to use jienengchen/ViTamin-B-LTT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jienengchen/ViTamin-B-LTT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jienengchen/ViTamin-B-LTT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jienengchen/ViTamin-B-LTT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03c50c1798c81025e5a71d97d12717f82c2e4b4e0d237cd8cf095049e5ccf5fc
- Size of remote file:
- 846 MB
- SHA256:
- 0cb0574ff72b0a94387700ad52b97aea13d6242bc120465c16b367d5adad7c98
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