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 model.safetensors from BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all/resolve/refs%2Fpr%2F2/model.safetensors
438 MB
- Xet hash:
- 13e4415b734e367ef7970413d0d42ff54a1790fbcba3d1e13cecaaf2cab3ff0e
- Size of remote file:
- 438 MB
- SHA256:
- 2f02fb259a21ef11ac36ee308d81585ac8d58a9072a66c2ee95a8b44d2c22fe7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.