Instructions to use BenjaminOcampo/task-subtle_task__model-bert__aug_method-rne 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-rne 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-rne")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-subtle_task__model-bert__aug_method-rne") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-subtle_task__model-bert__aug_method-rne", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f709059d6ed666255939e6fb315fd2d57053cd223e543d9f2f3193c505ae436
- Size of remote file:
- 3.39 kB
- SHA256:
- adf3f0eddc06f982f4db53a6cea6850261fd27b275a52de893dcdaf30c605988
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.