Instructions to use notaphoenix/liberal_argument_classifer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notaphoenix/liberal_argument_classifer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="notaphoenix/liberal_argument_classifer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("notaphoenix/liberal_argument_classifer") model = AutoModelForSequenceClassification.from_pretrained("notaphoenix/liberal_argument_classifer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b87ce02c7fd42cbc5cd83eae190895b9aa8ba58b79f942b107e0fea1ef43d0c
- Size of remote file:
- 595 MB
- SHA256:
- 44b70bb14592170fedf893f4c0258fd2155ae99f8e40dae4a84f7eecf0553c99
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