Instructions to use BenjaminOcampo/task-implicit_task__model-bert__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-bert__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-bert__aug_method-gm_revised")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-gm_revised") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-gm_revised", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c453cb790daed3029ee71b9c1952b08041afd4d9f66f363924fcd72f2f18c64
- Size of remote file:
- 438 MB
- SHA256:
- 6b1af0dea5067dfffe36cbf4099d828ad3b2ba256e5c5062ff62cc2e67afc016
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