Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda 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-eda 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-eda")# 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-eda") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda/resolve/refs%2Fpr%2F1/model.safetensors
438 MB
- Xet hash:
- 981a6f383a3980724b064ae45d4c5e0c3fb3b8f0c5d9a53d1cc9d674242a6fde
- Size of remote file:
- 438 MB
- SHA256:
- b440ec354ec11cee30a1622f9a1bf4ad0c303c8bd6658e03f8cdc7ccff592f1f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.