Instructions to use YakovElm/Apache15SetFitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YakovElm/Apache15SetFitModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YakovElm/Apache15SetFitModel") 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/Apache15SetFitModel with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("YakovElm/Apache15SetFitModel") 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/Apache15SetFitModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Apache15SetFitModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Apache15SetFitModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Apache15SetFitModel/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 283d26867026ef017995f2a2f6c800b60e47295988ef072ef5ebfe0290af897f
- Size of remote file:
- 438 MB
- SHA256:
- 10a1b5cd5cc6e0a0aa221ef436e06b95b989d9837730d8ed1f99f2017f9c6f94
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