Instructions to use BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri/resolve/4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/training_args.bin
- Command line
-
hf download hf://BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri@4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri/resolve/4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/training_args.bin
3.39 kB
- Xet hash:
- 0f99bb13c117fc372fe00658607ccebe7e28cb64a2d6f004eac9b4c4bfa371e8
- Size of remote file:
- 3.39 kB
- SHA256:
- e5484417d46a37a90f7b45f5b060e82a6a42b74bb14fe433d4a9576af3a10072
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