Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use alexgshaw/hyperpartisan-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexgshaw/hyperpartisan-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alexgshaw/hyperpartisan-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alexgshaw/hyperpartisan-classifier") model = AutoModelForSequenceClassification.from_pretrained("alexgshaw/hyperpartisan-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97da1e8288c32a0a440aae258ad31fa1b3a660e3b25e6ca18a798b8443e08b71
- Size of remote file:
- 268 MB
- SHA256:
- d89396389e1e938c8b52cde4bbada5eb1d99ed2af24f6d519f8f9acc6cdf998f
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