Instructions to use BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish") 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 BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish/resolve/main/tokenizer.json
- Command line
-
hf download hf://BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/BeToast/xml_xnli__inclusiveORexclusive__binary_classification__frenchANDenglish/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- a5c1bba1c44d19c8b61e650f4eba5a35b1b8d5108e8ee79e6a18313c135283dd
- Size of remote file:
- 17.1 MB
- SHA256:
- 6bb7ebc7ea8e67905fb06151a38c063935ab831341e1228add61e6cf9cf3d97b
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