Instructions to use owaiskha9654/PICO_Evidence_Classification_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owaiskha9654/PICO_Evidence_Classification_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="owaiskha9654/PICO_Evidence_Classification_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("owaiskha9654/PICO_Evidence_Classification_Model") model = AutoModelForSequenceClassification.from_pretrained("owaiskha9654/PICO_Evidence_Classification_Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56cffbba2f6c9be5b9f4739fdf2852712d8b4b3bb3d487c6da82fd4eafaf7159
- Size of remote file:
- 433 MB
- SHA256:
- 44f3dbe8bd869d9169376862d58161ae1f1132f10a77fd80b40ac5bc7729080e
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