Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model285 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model285 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model285")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model285") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model285", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 014c573723ff2cbc0e87d45ff43eab6015426cd149dda57271d1408e3e548c77
- Size of remote file:
- 5.37 kB
- SHA256:
- 68b450254a72ae838fc9b4e659e6aa45e58cc17d15c710b7a2516dde5eae6898
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