Instructions to use medspaner/roberta-es-clinical-trials-temporal-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medspaner/roberta-es-clinical-trials-temporal-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medspaner/roberta-es-clinical-trials-temporal-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medspaner/roberta-es-clinical-trials-temporal-ner") model = AutoModelForTokenClassification.from_pretrained("medspaner/roberta-es-clinical-trials-temporal-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ec24ce82e8c8e14a5e3af7ea469f182261109bc71304da7c6acfadf71c68ff3
- Size of remote file:
- 496 MB
- SHA256:
- cddd41ed7190d6274e166538e13ae61ceb96002df84024bcac19fd572343a584
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