Instructions to use dewifaj/multilabel-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewifaj/multilabel-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dewifaj/multilabel-text-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dewifaj/multilabel-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("dewifaj/multilabel-text-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dewifaj/multilabel-text-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/dewifaj/multilabel-text-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://dewifaj/multilabel-text-classifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/dewifaj/multilabel-text-classifier/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 0fb0717b39ff78dff537e470e7bd584dc7dfd01618f12d21c8de04c676828572
- Size of remote file:
- 5.11 kB
- SHA256:
- 940a082dcc60bc29fbcc89cdae899f3704c617fe741ea9dfd3057b4db8870472
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