Instructions to use mrp/SCT_Distillation_BERT_Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_Distillation_BERT_Base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_Distillation_BERT_Base") 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_Base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_Distillation_BERT_Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbb1610a3541521dee5c19dff29993f2f6851adf86c5c42c49c26aba19552ad4
- Size of remote file:
- 752 Bytes
- SHA256:
- 74533ab67986444256a630fb5df34ea6e4150dff617a9b63bc88c63736a20c39
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