Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model313 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model313 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model313")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model313") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model313", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d144a67ede7717dadb97e6bb009e855ccc467eb4654d5511ec5e485d991ffec
- Size of remote file:
- 5.37 kB
- SHA256:
- 2f4afddf2f58f1eed0cc413c87b3e423c275b33353dc413da0b73495a478357f
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