Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt 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-bt 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-bt")# 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-bt") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt/resolve/refs%2Fpr%2F1/model.safetensors
438 MB
- Xet hash:
- 687a435fd962a53712f6af027fbde1f64a51465ff65b314d2976cad587cccd07
- Size of remote file:
- 438 MB
- SHA256:
- 3504f78d9b1ba7f56db0c4fd982c01c57efeb8452bffda98e2e6a4c88017810d
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