Instructions to use nikhilteja30/pubmedqa-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikhilteja30/pubmedqa-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikhilteja30/pubmedqa-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikhilteja30/pubmedqa-bert") model = AutoModelForSequenceClassification.from_pretrained("nikhilteja30/pubmedqa-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nikhilteja30/pubmedqa-bert: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/nikhilteja30/pubmedqa-bert/resolve/main/training_args.bin
- Command line
-
hf download hf://nikhilteja30/pubmedqa-bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nikhilteja30/pubmedqa-bert/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 74e62000891dd553aff324a024262d9c6344a4a37c904393e4d10f0e4ca5b79a
- Size of remote file:
- 5.27 kB
- SHA256:
- ae15a9d1a19ae1639e893f5633a83e71afee555cc45eaf06e6a2b65f9a6653e9
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