Instructions to use SU-FMI-AI/multiclinner-enigma-es-symptom-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-symptom-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-symptom-RigoBERTa-Clinical")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SU-FMI-AI/multiclinner-enigma-es-symptom-RigoBERTa-Clinical") model = AutoModelForTokenClassification.from_pretrained("SU-FMI-AI/multiclinner-enigma-es-symptom-RigoBERTa-Clinical", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c65de84ebc0bf60171459f228a14d8daf3c974d397fe18d479c354d96b69e3a3
- Size of remote file:
- 5.27 kB
- SHA256:
- 551a9ca23e54d8e700574168c6d15b6767885f72adb26619380c0e82fdad83ec
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