Instructions to use jianli1/in-dorm-refl-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jianli1/in-dorm-refl-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jianli1/in-dorm-refl-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jianli1/in-dorm-refl-model") model = AutoModelForSequenceClassification.from_pretrained("jianli1/in-dorm-refl-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model description
Trained using:
python train_deep_model.py --model_name FacebookAI/roberta-base --confidence_threshold 4 --model_dir ./model_4_9_no_context_filter_macro_7 --original_labels True --include_context False --requires_context_filter True --eval_metric macro_f1 --early_stopping_patience 50 >> macro_7_results.txt
Dataset
Trained on https://huggingface.co/datasets/MU-NLPC/CEReD
Notes
Annotator confidence threshold = 4
Original labels
No context
Doesn't include rows where annotators required context
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