Sentence Similarity
sentence-transformers
Safetensors
bert
intent-classification
multilingual
distillation
layer-pruning
text-embeddings-inference
Instructions to use gomyk/intent-student-L2_ends with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gomyk/intent-student-L2_ends with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gomyk/intent-student-L2_ends") 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
- Xet hash:
- 3d046d183c8c7127253b2a58ae2362cdc43f6a48a1cf269bc0c8626f02154041
- Size of remote file:
- 400 MB
- SHA256:
- dafa9023a0f74781372c85195cd0550d895cb3a1b09c96f83dd9cf413ca9bbe0
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