Instructions to use mrp/SCT_BERT_Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_BERT_Large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_BERT_Large") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use mrp/SCT_BERT_Large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_BERT_Large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d154b7c05a6c176bc13fee75ce957cfcb3d4f74765070f5c389b8eed0e8a13bf
- Size of remote file:
- 679 Bytes
- SHA256:
- f4540494882ab0ef68b4f1f093d86ae3abd122e086db3493187c0289c0c5d07e
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