Instructions to use ntdat8324/xlmr_large_sbert_k6_evidence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ntdat8324/xlmr_large_sbert_k6_evidence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ntdat8324/xlmr_large_sbert_k6_evidence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ntdat8324/xlmr_large_sbert_k6_evidence") model = AutoModelForSequenceClassification.from_pretrained("ntdat8324/xlmr_large_sbert_k6_evidence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- def26f1402a8b3768f136280933a5fb1ae919de7cff35c50196b7d49871a9830
- Size of remote file:
- 17.1 MB
- SHA256:
- 93189c5d9a15db043017cfd920e00cf72fe9a4220bd74b460b635f6aa85a61a2
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