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:
- e02e7fc6c3a8f079181aec29bf42dcaaf4bee082c8853a426766aa118ae99253
- Size of remote file:
- 115 MB
- SHA256:
- 0b61590f84ac7880787c291a346539bfa11edea9a923c65d27c71b791be5ad14
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