Instructions to use korben99/bne-float-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use korben99/bne-float-384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("korben99/bne-float-384") 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
| { | |
| "model_type": "FloatEmbedder", | |
| "output_dim": 384, | |
| "backbone": "prajjwal1/bert-mini" | |
| } |