Instructions to use CarloSgara/t5_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use CarloSgara/t5_base_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CarloSgara/t5_base_model") 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:
- d3526c487474a4e2563bfe11169a6af4c9e745420855a779d52739041fad3c89
- Size of remote file:
- 2.36 MB
- SHA256:
- 2667cd2b9afc5f8affd1484c34a67f8fb0dda778ab5506f568971a6ad1366f03
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