Instructions to use ArashF/ClinicalBERT_captainA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArashF/ClinicalBERT_captainA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ArashF/ClinicalBERT_captainA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ArashF/ClinicalBERT_captainA") model = AutoModelForSequenceClassification.from_pretrained("ArashF/ClinicalBERT_captainA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ArashF/ClinicalBERT_captainA: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/ArashF/ClinicalBERT_captainA/resolve/main/training_args.bin
- Command line
-
hf download hf://ArashF/ClinicalBERT_captainA/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ArashF/ClinicalBERT_captainA/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- a8bcb538a8bb45e782529c0a818bd3b6470d5e09af2c41e610e53bd03e9137c9
- Size of remote file:
- 3.96 kB
- SHA256:
- a5ed0777061c4262aa65c194193982c927ccc37b43c79aa0e0653ba4c7b6e625
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