Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model291 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model291 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model291")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model291") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model291", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3764ad5932199fb4bd76b4547d19e345eff4fa105639badac6273ae68185fbe8
- Size of remote file:
- 5.37 kB
- SHA256:
- 496244abdd02dbbad8a2d97d4da540452918d05babc2eb55edd6db872d8ce2fc
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