Instructions to use jay0911/ade_biobert_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jay0911/ade_biobert_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jay0911/ade_biobert_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jay0911/ade_biobert_output") model = AutoModelForSequenceClassification.from_pretrained("jay0911/ade_biobert_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jay0911/ade_biobert_output: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jay0911/ade_biobert_output/resolve/main/training_args.bin
- Command line
-
hf download hf://jay0911/ade_biobert_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jay0911/ade_biobert_output/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 4fe87e6556fab1646b37e83d2d85aa26979ad37e92727243835164c1dd57d4f8
- Size of remote file:
- 5.3 kB
- SHA256:
- 24c3dc9eb1537c06c6571647378bfbb7e5ac0257b6175e237b451a0eb350c907
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