Instructions to use perticarari/test_embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use perticarari/test_embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("perticarari/test_embedder") 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
| license: mit | |
| datasets: | |
| - sentence-transformers/stsb | |
| language: | |
| - en | |
| base_model: | |
| - google-bert/bert-base-uncased | |
| pipeline_tag: sentence-similarity | |
| library_name: sentence-transformers | |