Instructions to use diwank/dyda-deberta-pair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diwank/dyda-deberta-pair with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="diwank/dyda-deberta-pair")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("diwank/dyda-deberta-pair") model = AutoModelForSequenceClassification.from_pretrained("diwank/dyda-deberta-pair", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from diwank/dyda-deberta-pair: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/diwank/dyda-deberta-pair/resolve/main/training_args.bin
- Command line
-
hf download hf://diwank/dyda-deberta-pair/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/diwank/dyda-deberta-pair/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 52b10aa068d0d158108d5d205e664bbcee6c44181be6989ee54798892e5115a3
- Size of remote file:
- 3.18 kB
- SHA256:
- 66a091315c7f9c5a6142219c42eae915a36ee0fd89df106d9c27cdb2c14f0bc2
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