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:
- 460726d84aa2653afe36aca3ac6b7b0495b228f39c484a6087346802bdbfe668
- Size of remote file:
- 122 Bytes
- SHA256:
- 305b54038dc5bf137ca1703581b09a99d30ec8abb2daa512c3a4e01afe497e4c
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