Feature Extraction
sentence-transformers
Safetensors
Vietnamese
English
bert
sentence-similarity
qdrant
vietnamese
tourist-notebook
text-embeddings-inference
Instructions to use lmtri0312/tramy-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lmtri0312/tramy-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lmtri0312/tramy-encoder") 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] - Notebooks
- Google Colab
- Kaggle
Fix sentence_bert_config.json kwargs
Browse files
sentence_bert_config.json
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"text": {
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"method": "forward",
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"method_output_name": "last_hidden_state"
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"module_output_name": "token_embeddings"
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"max_seq_length": 512,
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"do_lower_case": false
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}
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