Instructions to use AnonymousCS/populism_model330 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model330 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model330")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model330") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model330", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fb00a89980ea5b513ab57ebf2fc43dad7dcdfa1ad098e4ca8b13b1bced5f278
- Size of remote file:
- 2.3 GB
- SHA256:
- 1ec183d7b83691b11368cc4632e0dc852e2c57f205d22bab9a3082e3065edf10
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