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
Download training_args.bin from oneryalcin/static-embedding-chess: direct link, hf CLI and curl.
- Browser
- Download file 5.71 kB
-
https://huggingface.co/oneryalcin/static-embedding-chess/resolve/main/training_args.bin
- Command line
-
hf download hf://oneryalcin/static-embedding-chess/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/oneryalcin/static-embedding-chess/resolve/main/training_args.bin
5.71 kB
- Xet hash:
- ee75eb677ce05c6c9ebee2668d79981c742a8c18221e4fe0ebcae7911f4eb4b6
- Size of remote file:
- 5.71 kB
- SHA256:
- 426fc88cc7388ad3485f0a0e98b7edcbc0f7e7ad469707d5448cc9275c652053
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