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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc2f822a316b669cf4dd2e853e96dfc68f68e7ed8f1504cff91aabbbb4ea0150
- Size of remote file:
- 44.7 MB
- SHA256:
- 4f5ada2c9af2a71d51c7ca6928e0b67d5a252118d093d823792b9f6753060302
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