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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f92239442deeabe2366f8e0249c2ff6dd215bcd89f853cb983615c1d2e4d77fc
- Size of remote file:
- 520 Bytes
- SHA256:
- 57a0fabfdda24613da633b30a18b4fc2e0ef24618984e4a7169f016abcfa546f
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