Instructions to use deepachalapathi/without_questions_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use deepachalapathi/without_questions_4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deepachalapathi/without_questions_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 deepachalapathi/without_questions_4 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("deepachalapathi/without_questions_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 deepachalapathi/without_questions_4: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/deepachalapathi/without_questions_4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepachalapathi/without_questions_4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepachalapathi/without_questions_4/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 111c6db36a7dfe9fc04fc46a0d89d611421f702797c6ab1b61497d35b380337a
- Size of remote file:
- 438 MB
- SHA256:
- 8bc8b96b39b0d6163ccdcce23d7949d3a9b1d8c3fede15b551baa45222f80c09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.