Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model270 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model270 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model270")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model270") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model270", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca50575c441b57536fd0a731c117d1dfc9d2f755b9a9c8c6c218a93ba9bf258e
- Size of remote file:
- 5.37 kB
- SHA256:
- a8dab183c69f1857da71e45a7ee59eee18626fb2316c7c9ad3a0cc6d3965d3ea
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