Sentence Similarity
sentence-transformers
PyTorch
distilbert
feature-extraction
Generated from Trainer
dataset_size:2
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use ostoveland/test8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ostoveland/test8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ostoveland/test8") 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:
- 3cc25d766ab7c4602a070a238048922812339b32bb0138778cf8656dea382250
- Size of remote file:
- 265 MB
- SHA256:
- c602afe32129d28d90ef191ee38c5215c7c22b47a0fb15301d8ccc473f533069
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