Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model201 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model201 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model201")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model201") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model201", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 619e40df06a79aade6de9b9733328473e912e2b5b19859897a38458602d33617
- Size of remote file:
- 5.37 kB
- SHA256:
- f3f6dcb5ce536457a0b51547187d8b931e2f48c62de6c90cf3cee4355a21b424
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