Sentence Similarity
sentence-transformers
Safetensors
Transformers
Vietnamese
Vietnamese
feature-extraction
phobert
vietnamese
sentence-embedding
custom_code
Instructions to use dangvantuan/vietnamese-document-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dangvantuan/vietnamese-document-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dangvantuan/vietnamese-document-embedding", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use dangvantuan/vietnamese-document-embedding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dangvantuan/vietnamese-document-embedding", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -52,7 +52,7 @@ from sentence_transformers import SentenceTransformer
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sentences = ["Hà Nội là thủ đô của Việt Nam", "Đà Nẵng là thành phố du lịch"]
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model = SentenceTransformer('dangvantuan/vietnamese-
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embeddings = model.encode(sentences)
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print(embeddings)
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sentences = ["Hà Nội là thủ đô của Việt Nam", "Đà Nẵng là thành phố du lịch"]
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model = SentenceTransformer('dangvantuan/vietnamese-document-embedding', trust_remote_code=True)
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embeddings = model.encode(sentences)
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print(embeddings)
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