Instructions to use notaphoenix/conservative_argument_classifer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notaphoenix/conservative_argument_classifer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="notaphoenix/conservative_argument_classifer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("notaphoenix/conservative_argument_classifer") model = AutoModelForSequenceClassification.from_pretrained("notaphoenix/conservative_argument_classifer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7397ba66d4d284ab40331ba1031ae29c385f0b0f1bf395a491eacfd506648488
- Size of remote file:
- 595 MB
- SHA256:
- 9839f4d4cbbcae49e557801d52e1a826f6f9135961da009336c2276a99cd7895
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