Instructions to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-implicit_task__model-bert__aug_method-all")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BenjaminOcampo/task-implicit_task__model-bert__aug_method-all: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-all/resolve/main/training_args.bin
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-bert__aug_method-all/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-all/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- dd7979dcce4bf4416cc44521eab020680451ab41641fa3cadfa7d769fa46484a
- Size of remote file:
- 3.39 kB
- SHA256:
- 9c434cc51697fff169bda5825b42a325f047692cc7083ddf55a9f2fdb5be4f80
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