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:
- 6daa77d03b083dc7c2bd939401fab5e22bdd112e2b31807262583aea12cc7528
- Size of remote file:
- 457 kB
- SHA256:
- 6f70e1629bfda29faedfca1474d2195bd527590eeb48b628fd862da12a2070f3
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