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:
- 9aba988044178688b4bf99ea339586131a46f16e940b9a231390213761efaf2f
- Size of remote file:
- 44.7 MB
- SHA256:
- 852742aa06708911d43e1822c17f084a1ef8ecb5a0e8b105085b1a31bb73aeb8
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