Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model210 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model210 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model210")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model210") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model210", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1f3432fa930f06d15a4f920ed425700ff90181141afe43549a1baa1aa494199
- Size of remote file:
- 5.37 kB
- SHA256:
- 1978ecfaef6ddf2cf4fb527d17aa33a75aa56dcb6e535afa1f8cee8a2bbf9306
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