Instructions to use mrp/SCT_Distillation_BERT_Tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_Distillation_BERT_Tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_Distillation_BERT_Tiny") 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_Tiny with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_Distillation_BERT_Tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaa386f49600ddd29719790730930fff9c8f6a6d64dc4956c4cb64945c0573c4
- Size of remote file:
- 17.6 MB
- SHA256:
- 9230df5233ed82e74ba82157a199d17c6c176487487e5f49216503847ef2850d
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