Instructions to use SU-FMI-AI/multiclinner-enigma-es-disease-RigoBERTa-Clinical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SU-FMI-AI/multiclinner-enigma-es-disease-RigoBERTa-Clinical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SU-FMI-AI/multiclinner-enigma-es-disease-RigoBERTa-Clinical")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SU-FMI-AI/multiclinner-enigma-es-disease-RigoBERTa-Clinical") model = AutoModelForTokenClassification.from_pretrained("SU-FMI-AI/multiclinner-enigma-es-disease-RigoBERTa-Clinical", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b34d12508d1555f75a44ada45fb26fc3afc9c5e07ee750d51fbb31c6ff2a46ef
- Size of remote file:
- 5.27 kB
- SHA256:
- 044e7315c8f7c25339e45d8fcbdf53eb43d7f2e6900d8cef5a0e9f1e10c0e3e6
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