Instructions to use BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf2369075a8ea017350d3e7f59d990d30a43694dbb6fff438b9febfcee79cf3f
- Size of remote file:
- 738 MB
- SHA256:
- 22ee28ac1904d460ce63a9b9608b4a0262896c6d91d23e8599db2641820b64ee
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