Instructions to use mrp/SCT_BERT_Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_BERT_Mini with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_BERT_Mini") 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_Mini with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_BERT_Mini", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9020bad8c9b997f1fd69153dd57d3f6b70d3d5aa4b6f35ec9cb9b79811acaba
- Size of remote file:
- 112 Bytes
- SHA256:
- 303df45a03609e4ead04bc3dc1536d0ab19b5358db685b6f3da123d05ec200e3
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