Instructions to use harish/PT-FalseFalse-0_2_BEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-FalseFalse-0_2_BEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harish/PT-FalseFalse-0_2_BEST")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harish/PT-FalseFalse-0_2_BEST") model = AutoModelForSequenceClassification.from_pretrained("harish/PT-FalseFalse-0_2_BEST") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a74166d84746cb52f2f4918a73c49da2e1bf7879fdd65e3b81eb931dc86e4ebd
- Size of remote file:
- 711 MB
- SHA256:
- f955ba072d9e3de1d759bdb48006ac1ea2786ed9ed29ffdddbfdd06b42e05819
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