Instructions to use mrp/SCT_Distillation_BERT_Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mrp/SCT_Distillation_BERT_Small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mrp/SCT_Distillation_BERT_Small") 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_Small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrp/SCT_Distillation_BERT_Small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c273a8dbb2ce6746e0001136b670e15ab8a3e29f6be89eaffb90bab65ff3654f
- Size of remote file:
- 745 Bytes
- SHA256:
- f8e3a19006093c77f7487cda22be1006cbdaf4c8a9bef9eaff7945cb22ac549e
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