Instructions to use preneond/newlinefix-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use preneond/newlinefix-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="preneond/newlinefix-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("preneond/newlinefix-encoder") model = AutoModelForTokenClassification.from_pretrained("preneond/newlinefix-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 659 Bytes
dd6ef4f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"max_words": 180,
"overlap": 64,
"model_name": "distilroberta-base",
"val_metrics": {
"accuracy": 0.9795400902058844,
"macro_f1_structural": 0.7832464081700393,
"precision_JOIN": 0.887536112257532,
"recall_JOIN": 0.9830857142857143,
"f1_JOIN": 0.9328706214076565,
"precision_SPACE": 0.9972153093227003,
"recall_SPACE": 0.9830608435529667,
"f1_SPACE": 0.9900874903362599,
"precision_NEWLINE": 0.6938279112192156,
"recall_NEWLINE": 0.8199784405318002,
"f1_NEWLINE": 0.7516469038208169,
"precision_PARA": 0.5414314516129032,
"recall_PARA": 0.8623956326268465,
"f1_PARA": 0.6652216992816448
}
}
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