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:
- 08d3bffa7bac6b4510e609316ed0ca940a40aa3dd7e22a38f0bc16b22bbe7a42
- Size of remote file:
- 1.11 GB
- SHA256:
- 296389b288ea4226ff0b4f609baa22111ef55e6a55669afa18a06274f38f40dc
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