Instructions to use AbeHou/SemStamp-c4-sbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbeHou/SemStamp-c4-sbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AbeHou/SemStamp-c4-sbert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AbeHou/SemStamp-c4-sbert") model = AutoModel.from_pretrained("AbeHou/SemStamp-c4-sbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 015bddd2c2bd305333b8feb1bac80314a45c13bb2e1afce326049238785bf896
- Size of remote file:
- 438 MB
- SHA256:
- f23f44b44fcad45f2f6178c3936ac7c7d8b16b09b3b70a0043b61c4a6a2e9dee
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