Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use joniponi/discharge-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joniponi/discharge-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joniponi/discharge-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joniponi/discharge-classifier") model = AutoModelForSequenceClassification.from_pretrained("joniponi/discharge-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joniponi/discharge-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/joniponi/discharge-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://joniponi/discharge-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joniponi/discharge-classifier/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 7c7cff629443314c5fb66cd0809bfac5c127ab79c83afc7567a50845dcf20701
- Size of remote file:
- 2.99 kB
- SHA256:
- 29a3a5f3fc84208d7b22e51b119e418881d8cd63acfe2b3b5a37af0f12f0468a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.