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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from owaiskha9654/PICO_Evidence_Classification_Model: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/owaiskha9654/PICO_Evidence_Classification_Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://owaiskha9654/PICO_Evidence_Classification_Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/owaiskha9654/PICO_Evidence_Classification_Model/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- be27e3e34b82c7c28be197f6b4dae769710abaafc0076027423f40c105b492c6
- Size of remote file:
- 433 MB
- SHA256:
- b46b6fd412c1d37193c6fdeadcdca5f6093e8660145da9a8d12f0c96906f5b5c
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