Instructions to use YakovElm/IntelDAOS10SetFitModel_balance_ratio_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS10SetFitModel_balance_ratio_3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS10SetFitModel_balance_ratio_3") 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_balance_ratio_3 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS10SetFitModel_balance_ratio_3") 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_balance_ratio_3: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS10SetFitModel_balance_ratio_3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/IntelDAOS10SetFitModel_balance_ratio_3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/IntelDAOS10SetFitModel_balance_ratio_3/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1f430176d3aac0d18981b7a1f28612941a94c26799ad6855392c3026a7e93783
- Size of remote file:
- 438 MB
- SHA256:
- 5f3bf64e48672c9f3a687788512b90f8bf5fc5d3bb2fee7a21224c3fde8e9145
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