Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model310 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model310 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model310")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model310") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model310") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae26251798c7599ec9c98839ff3a932d758d4ab04fe94d708b5831e63c4cec89
- Size of remote file:
- 669 MB
- SHA256:
- 49782483f5bf7494d2985a4d06591503963cfb78864d8c5d7e62843b705241ae
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