Instructions to use nedima68/author_articles_classifier_TR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nedima68/author_articles_classifier_TR with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nedima68/author_articles_classifier_TR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Push model using huggingface_hub.
Browse files- config.json +1 -0
config.json
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{"model_name": "distilroberta-base", "n_labels": 4, "batch_size": 64, "lr": 1.5e-05, "warmup": 0.2, "train_size": 1458, "weight_decay": 0.01, "n_epochs": 2}
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