Instructions to use HiTZ/xlm-roberta-large-xnli-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/xlm-roberta-large-xnli-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HiTZ/xlm-roberta-large-xnli-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/xlm-roberta-large-xnli-es") model = AutoModelForSequenceClassification.from_pretrained("HiTZ/xlm-roberta-large-xnli-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HiTZ/xlm-roberta-large-xnli-es: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/HiTZ/xlm-roberta-large-xnli-es/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HiTZ/xlm-roberta-large-xnli-es/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HiTZ/xlm-roberta-large-xnli-es/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 2d23c902b39030c510bed6220931c7b8521995b8b031eec807a237229277240a
- Size of remote file:
- 2.24 GB
- SHA256:
- 0ed67bdfc56589e5457bfdada076f49789d2ae47d7e3689bb093a4db210c87f2
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