Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__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-hatebert__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-hatebert__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-hatebert__aug_method-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all/resolve/754ff249fdb51956e3529c85bcee19ebfb567404/training_args.bin
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all@754ff249fdb51956e3529c85bcee19ebfb567404/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all/resolve/754ff249fdb51956e3529c85bcee19ebfb567404/training_args.bin
3.39 kB
- Xet hash:
- 5d9c56cf733a52ab97ca25f61e12d1f5b467c2d39b5de348b8c29f9943769477
- Size of remote file:
- 3.39 kB
- SHA256:
- 4e97f00a927791e606d7b0dc3d44d327b52e447a22ab54acc689ff265f95aabb
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