Instructions to use BenjaminOcampo/task-implicit_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-implicit_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-implicit_task__model-bert__aug_method-rsa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-rsa") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-rsa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e09184844f920e10e25e6155a3545be58268e1dee63a850ff8cb443eba4d9000
- Size of remote file:
- 438 MB
- SHA256:
- ca7d712c7d1cc1b86c6d794620eb8c165033d884491d9d214c7c4cfd6b650f6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.