Instructions to use lgessler/coptic-microbert-tree-sgcl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgessler/coptic-microbert-tree-sgcl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lgessler/coptic-microbert-tree-sgcl")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lgessler/coptic-microbert-tree-sgcl") model = AutoModel.from_pretrained("lgessler/coptic-microbert-tree-sgcl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 199f738443f445d3f203b9e0d1aebeeb14b50c5ee49c0220c128f14ecb021982
- Size of remote file:
- 7.98 MB
- SHA256:
- b210d879146c0f168fe827c120757aedf0263fff664387a15a244fdf09b2bdc4
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