Instructions to use AnonymousCS/populism_classifier_bsample_309 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_309 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_309")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_309") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_309", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96b4a59299d2953d4dc12fb97b67dc6a185b89a96e944aef87429e2df30fa491
- Size of remote file:
- 5.43 kB
- SHA256:
- 9553a20465a749f81c88655de93074e87a7287afe3d3b5ac3d0fdea60dc55f00
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