Instructions to use YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4") 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/IntelDAOS10SetFitModel_Train_balance_ratio_4 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4") 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/IntelDAOS10SetFitModel_Train_balance_ratio_4: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/IntelDAOS10SetFitModel_Train_balance_ratio_4/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1d69c6c4db0610eaec0dd07013a75f0a49aa0d138f3c345d9f92e8fb4e368531
- Size of remote file:
- 438 MB
- SHA256:
- b57404287e3da04aa33c8a31476cc1034a0b0a73ea7a72269ab2f594093ee513
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