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 model.safetensors 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/model.safetensors
- Command line
-
hf download hf://owaiskha9654/PICO_Evidence_Classification_Model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/owaiskha9654/PICO_Evidence_Classification_Model/resolve/main/model.safetensors
433 MB
- Xet hash:
- 56cffbba2f6c9be5b9f4739fdf2852712d8b4b3bb3d487c6da82fd4eafaf7159
- Size of remote file:
- 433 MB
- SHA256:
- 44f3dbe8bd869d9169376862d58161ae1f1132f10a77fd80b40ac5bc7729080e
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