Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model269 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model269 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model269")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model269") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model269", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38567e7a275125704d4d0f3c5de736a9bf4e243d0a748ca3fdd42d2e12fa2e89
- Size of remote file:
- 5.37 kB
- SHA256:
- 1e220dedfc751c52faa68af08d9b2df4d2a5fd353518da7ed70a5ea44698afc8
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