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:
- c0530290104b4d8a69055cc90251195b0ee0c7f65cf1a9a0cc3cb7880978abe5
- Size of remote file:
- 433 MB
- SHA256:
- 3fe24dc29f9bd4e0154a4e4814144a909a8d5096d5c10e2b93763fc9327972a4
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