Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model231 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model231 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model231")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model231") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model231", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c308a881dc5857ae1940bd510fd02df35ea28b0e390b15e8cef05d8e0d9d7ad7
- Size of remote file:
- 5.37 kB
- SHA256:
- 2dbdfbae8162ccfb1d091e0aca3e3a1e01b815ddc17db7bcec695e0b7d54c932
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