Instructions to use Aadithyak/deberta-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aadithyak/deberta-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aadithyak/deberta-final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aadithyak/deberta-final") model = AutoModelForSequenceClassification.from_pretrained("Aadithyak/deberta-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Aadithyak/deberta-final: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/Aadithyak/deberta-final/resolve/main/training_args.bin
- Command line
-
hf download hf://Aadithyak/deberta-final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Aadithyak/deberta-final/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- b84f74ccc6dc81f63ab591bee3f618f70247fd5a3cb2af35292550a7f4116885
- Size of remote file:
- 5.24 kB
- SHA256:
- 88479e92ab661f49e561ad6fddcf88a48bbb1ee654c9c5c56c762958a16fd5f8
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