Instructions to use BenjaminOcampo/task-subtle_task__model-bert__aug_method-rsa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-subtle_task__model-bert__aug_method-rsa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-subtle_task__model-bert__aug_method-rsa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-subtle_task__model-bert__aug_method-rsa") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-subtle_task__model-bert__aug_method-rsa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 372da4e72c4fade80352bf926e2d3d46e268841bd11e1793ff5d4d1a48c52262
- Size of remote file:
- 438 MB
- SHA256:
- 0567d02f4a240cbfd700a2a3a5dd3a0d9ec461868de75c60567f1e7827471125
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.