Instructions to use AnonymousCS/populism_classifier_bsample_388 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_388 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_388")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_388") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_388", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb0a9d4c0aa534a286c84b16e90038a82a0e5a992bdb7ff81c9c8dcc9f456b7f
- Size of remote file:
- 1.34 GB
- SHA256:
- c1842639a69594b8eb3553d9d7fdbea2f3b13bd5beda62355b90a771dee907bc
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