Instructions to use BenjaminOcampo/task-implicit_task__model-bert__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-bert__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-bert__aug_method-eda")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-eda") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-eda") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6db9f35013d96496fe1db3ce9819b09a560dac8dec4afe08ed0db39f18c4c25a
- Size of remote file:
- 438 MB
- SHA256:
- 719defa2b2bc0e0379961c5257416bcfd9e03e5c41ccdb67d82cc343e45bc21b
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