Instructions to use mrp/SCT_Distillation_BERT_Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_Distillation_BERT_Small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_Distillation_BERT_Small") 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_Distillation_BERT_Small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_Distillation_BERT_Small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6f1dbfb3d665bcafee89e1cacbc2748684caf350e0058c91bd9e0bfa91f4805
- Size of remote file:
- 115 MB
- SHA256:
- ac1e0afa31a53b2ffd253ddc8eb9b52d067ccee3db46a03f27cf4fd03254a628
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