Instructions to use YakovElm/IntelDAOS5SetFitModel_clean_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/IntelDAOS5SetFitModel_clean_data with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/IntelDAOS5SetFitModel_clean_data") 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_clean_data with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/IntelDAOS5SetFitModel_clean_data") 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/IntelDAOS5SetFitModel_clean_data: direct link, hf CLI and curl.
- Browser
- Download file 6.99 kB
-
https://huggingface.co/YakovElm/IntelDAOS5SetFitModel_clean_data/resolve/main/model_head.pkl
- Command line
-
hf download hf://YakovElm/IntelDAOS5SetFitModel_clean_data/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/YakovElm/IntelDAOS5SetFitModel_clean_data/resolve/main/model_head.pkl
6.99 kB
- Xet hash:
- d3868accb3b14970ffa42479cbdab12bc4a374967708ddef6d67fb7f7512889a
- Size of remote file:
- 6.99 kB
- SHA256:
- 5902d35d217bc8b62a62ca30d6dfd5d95a85db632e51c3e659f292812cf40d73
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