Instructions to use AnonymousCS/populism_classifier_bsample_363 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_classifier_bsample_363 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_classifier_bsample_363")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_classifier_bsample_363") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_classifier_bsample_363", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92e6ae78a755f0eb959e15a319e07947091f7ba9fba01bb064a160711a8ffa8e
- Size of remote file:
- 5.43 kB
- SHA256:
- b789f2b97b185b039c95a290584667141c0cb6420cb92e065c983f7ab5e9a427
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.