Instructions to use Josef0801/model_1_deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Josef0801/model_1_deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Josef0801/model_1_deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Josef0801/model_1_deberta") model = AutoModelForSequenceClassification.from_pretrained("Josef0801/model_1_deberta") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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This model is based on svenbl80/deberta-v3-Base-finetuned-chatdoc-V5's model but further finetuned a synthetic dataset.
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It performs poorly on a different benchmark from the same document:
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precision recall f1-score support
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0 0.19 0.22 0.20 23
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1 0.62 0.44 0.52 75
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2 0.00 0.00 0.00 19
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accuracy 0.32 117
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macro avg 0.27 0.22 0.24 117
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weighted avg 0.44 0.32 0.37 117
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