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 pytorch_model.bin from BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri/resolve/4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/pytorch_model.bin
- Command line
-
hf download hf://BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri@4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BenjaminOcampo/task-subtle_task__model-deberta__aug_method-ri/resolve/4c386b6674596a9893ce8fa2e0d45dcd8d0cc8a7/pytorch_model.bin
738 MB
- Xet hash:
- a000c470cf8187776d1332c51a4897229fe1d5a359ae22983d0e6b757c1c7f16
- Size of remote file:
- 738 MB
- SHA256:
- 9f968b002abd4e6cca6ca89c67b7da981f77c4dc1bab2e63ecaa92882bef906a
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