Instructions to use YakovElm/IntelDAOS5SetFitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS5SetFitModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS5SetFitModel") 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/IntelDAOS5SetFitModel with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS5SetFitModel") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/IntelDAOS5SetFitModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS5SetFitModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/IntelDAOS5SetFitModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/IntelDAOS5SetFitModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- f276d20741dc7eadb7783e82bd9eb517529b9df8dce29e9d986b6650a076c94a
- Size of remote file:
- 438 MB
- SHA256:
- 1bbfb7349ead8097d563aa9c7aa69ab060d42d12f5ab7bfbf5c5cbff091e4fee
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