Instructions to use AnonymousCS/populism_classifier_bsample_300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_300 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_300")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_300") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_300", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c9a219ed769d51b58e186be65bf8f58263fc956ec0cd250390daa52a9939202
- Size of remote file:
- 433 MB
- SHA256:
- 3d256e894415ba9212de7d7ff3e6bbd5e4c90042ed40d7d419e081572ea7e70d
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