Instructions to use frmccann/CLSRIL-23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frmccann/CLSRIL-23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="frmccann/CLSRIL-23")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("frmccann/CLSRIL-23") model = AutoModel.from_pretrained("frmccann/CLSRIL-23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cc4ea6664496675d0e091f38bc4f6a32e7badf4fb1de2740f8a9f5575777f65
- Size of remote file:
- 378 MB
- SHA256:
- ac69542f3885c3214bff9e30de742c815ac09216927f6bb135d64d7a9da0785c
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