Sentence Similarity
sentence-transformers
Safetensors
English
static-embedding
chess
retrieval
exploratory
Instructions to use oneryalcin/static-embedding-chess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use oneryalcin/static-embedding-chess with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("oneryalcin/static-embedding-chess") 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:
- 550002ab1af97f20a322c644fc6cf2f488a6a676c1eac0787351572ddb36902e
- Size of remote file:
- 5.71 kB
- SHA256:
- bed99a155dbec21964e026b0647e360c1ee931c7048ba902384bf1f776fcae2c
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