Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use li-ping/river_retriver_416data_testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use li-ping/river_retriver_416data_testing with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("li-ping/river_retriver_416data_testing") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 212bfaaf7beffc70a3f2b8fbd9929f72e086ac0287cc39a5d98486b405c9209a
- Size of remote file:
- 17.1 MB
- SHA256:
- 46afe88da5fd71bdbab5cfab5e84c1adce59c246ea5f9341bbecef061891d0a7
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