Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model232 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model232 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model232")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model232") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model232", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 341e2ce695b14d8a5902643fb2648dd41af33af643e129644841361165599125
- Size of remote file:
- 5.37 kB
- SHA256:
- 506ecf00d73baa5fd16e1f95678423b47c339d301e94126086c2e24d4cbd25c9
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