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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f9f2d839ad862708e4315097becd631ce1c5047870f9780e7cabf15a561d1c2
- Size of remote file:
- 3.39 kB
- SHA256:
- a2def4da6a4d2c7df8bcebfb65c717b48b2029cf0b39f1113034d36f08c2934c
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