Instructions to use Lin-Chen/ShareCaptioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lin-Chen/ShareCaptioner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Lin-Chen/ShareCaptioner", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Lin-Chen/ShareCaptioner", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44065d9f4d8346c13b2753a451d1005b05e032be57ab4468bf33a8d5cbe075b4
- Size of remote file:
- 1.66 MB
- SHA256:
- 21ff673031fd4187f19721a86af4caa6a4deb1f3c2db284f763de3e53bd8f741
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