Sentence Similarity
sentence-transformers
Safetensors
bert
advai-notebooks
embedding
demo
synthetic-data
random-initialization
text-embeddings-inference
Instructions to use widebluesky/wbs-embedding-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use widebluesky/wbs-embedding-demo with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("widebluesky/wbs-embedding-demo") 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
File size: 84 Bytes
2a60966 | 1 2 3 4 5 6 | {
"embedding_dimension": 32,
"pooling_mode": "mean",
"include_prompt": true
}
|