Sentence Similarity
sentence-transformers
PyTorch
Transformers
roberta
feature-extraction
vietnamese
Instructions to use keepitreal/vietnamese-sbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use keepitreal/vietnamese-sbert with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("keepitreal/vietnamese-sbert") 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 keepitreal/vietnamese-sbert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("keepitreal/vietnamese-sbert") model = AutoModel.from_pretrained("keepitreal/vietnamese-sbert") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34b86084d0ecd4b84a2f352fb2ae8a0a7e33c78b2dc3527429dae1f616139555
- Size of remote file:
- 540 MB
- SHA256:
- f442320a1ae3cd68748245e47ca504703bb182f661af0e9acfd3e438aafeb104
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