Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model310 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model310 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model310")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model310") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model310", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9284c83bc724df1c9f14eefc6c02d935c1c3d52af0170c8b3d4d398ecad7f1cf
- Size of remote file:
- 5.37 kB
- SHA256:
- 68db609b3606cbe78108c071552e18ca3d0b43b19e334e5cb806c2e37a899ace
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