Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use aedupuga/fiction_predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aedupuga/fiction_predictor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aedupuga/fiction_predictor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aedupuga/fiction_predictor") model = AutoModelForSequenceClassification.from_pretrained("aedupuga/fiction_predictor") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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More information needed
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## Training procedure
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## Model description
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This model uses data from jennifee/HW1-aug-text-dataset and predicts whether a book is fiction or not based on review.
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## Intended uses & limitations
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This model was constructed as a practice in training for classification of text datasets.
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## Training procedure
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