Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model167 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model167 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model167")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model167") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model167", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- facd0ecb3d621e94580b342951d074038fc00dd20cc8ae6a4a4f597731b7fc4c
- Size of remote file:
- 5.37 kB
- SHA256:
- 39d9d22d3a2daea855d3f055cfbc963978dfe438dbc879a4e4d31aa25abde251
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