Instructions to use YakovElm/Hyperledger5SetFitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/Hyperledger5SetFitModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/Hyperledger5SetFitModel") 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] - setfit
How to use YakovElm/Hyperledger5SetFitModel with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/Hyperledger5SetFitModel") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from YakovElm/Hyperledger5SetFitModel: direct link, hf CLI and curl.
- Browser
- Download file 6.99 kB
-
https://huggingface.co/YakovElm/Hyperledger5SetFitModel/resolve/main/model_head.pkl
- Command line
-
hf download hf://YakovElm/Hyperledger5SetFitModel/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/YakovElm/Hyperledger5SetFitModel/resolve/main/model_head.pkl
6.99 kB
- Xet hash:
- ece07fa290d87fdd09b56d26058f6f97bd9105acd2c71e76cfafc3b3da7dafd8
- Size of remote file:
- 6.99 kB
- SHA256:
- 5a0c3c093ed164df138c048558215ed8d76c9b545869b9ffca20582f86d9ab56
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