Instructions to use YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half") 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/IntelDAOS20SetFitModel_Train_balance_ratio_Half with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half") 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/IntelDAOS20SetFitModel_Train_balance_ratio_Half: direct link, hf CLI and curl.
- Browser
- Download file 6.99 kB
-
https://huggingface.co/YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half/resolve/main/model_head.pkl
- Command line
-
hf download hf://YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/YakovElm/IntelDAOS20SetFitModel_Train_balance_ratio_Half/resolve/main/model_head.pkl
6.99 kB
- Xet hash:
- 4b0e4970c6909759b4c7ae68a928ca33f1b164f1ee40cd7d559ca7e616218284
- Size of remote file:
- 6.99 kB
- SHA256:
- 71b247478b426bc251c0564f28c3ac085838f36a3387f8bec4674f10af9bb14b
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