Instructions to use mrp/SCT_Distillation_BERT_Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_Distillation_BERT_Mini with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_Distillation_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_Distillation_BERT_Mini with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_Distillation_BERT_Mini", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f304a27ff8b651c10f02d44c6d15a0b02d5dc30d36a3e55b5714c54bdfc3c7c
- Size of remote file:
- 341 Bytes
- SHA256:
- f83ea5d68ac85ec15f650b350f0dc37b03d63abd60442f518e14c06f479beee6
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