Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model255 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model255 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model255")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model255") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model255", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3d07702764156286004da160b6e3da19f931178d822c760f768b0c8901349e4
- Size of remote file:
- 5.37 kB
- SHA256:
- 432ecdc5ddd00e5d73f769e840e331029fff459decb49b677e35cdd78341e4e0
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