Instructions to use hash-map/got_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hash-map/got_tokenizer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hash-map/got_tokenizer") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96b314c859bccee51306353836bc9b01a280ce2d4d780c0479bc432f8ce3a5a5
- Size of remote file:
- 743 kB
- SHA256:
- 618c81434ac7381e299479573396f1020c352d6723b961e07596c0a442110f75
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