Instructions to use dragonSwing/xlm-roberta-capu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dragonSwing/xlm-roberta-capu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dragonSwing/xlm-roberta-capu")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dragonSwing/xlm-roberta-capu") model = AutoModel.from_pretrained("dragonSwing/xlm-roberta-capu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad50efab35cc2127d9728eb45fecfe4d3b0f86fe5833fe8c75a401e9407519cf
- Size of remote file:
- 1.11 GB
- SHA256:
- a6e2a5c2b1cbf16a9fd0b88c0dc8585f3832a60d10eea8140854f8d8f32c188d
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