Instructions to use Ridhwan/locum_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ridhwan/locum_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ridhwan/locum_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ridhwan/locum_classification") model = AutoModelForSequenceClassification.from_pretrained("Ridhwan/locum_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ridhwan/locum_classification: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Ridhwan/locum_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Ridhwan/locum_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ridhwan/locum_classification/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 9ea172d6f81b6ef12f00f12c22fb8ad4daf21266b96b9a70b22ea6e1a711e155
- Size of remote file:
- 3.52 kB
- SHA256:
- b4ed96e987823b7adad6c18e9d843391205a8e74ba5c8ee3eaba25253671629d
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