Text Classification
Transformers
Safetensors
English
deberta-v2
books
genre-classification
metadata
text-embeddings-inference
Instructions to use Mitchins/book-genre-v5-title-author with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mitchins/book-genre-v5-title-author with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mitchins/book-genre-v5-title-author")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mitchins/book-genre-v5-title-author") model = AutoModelForSequenceClassification.from_pretrained("Mitchins/book-genre-v5-title-author", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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# Book Genre V5 Title+Author Classifier
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This package contains a weak title+author genre classifier intended for rough corpus segmentation, triage, and candidate labeling of raw book libraries.
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---
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license: mit
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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- text-classification
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- books
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- genre-classification
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- metadata
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- deberta-v2
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language:
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- en
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metrics:
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- accuracy
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- f1
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---
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# Book Genre V5 Title+Author Classifier
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This package contains a weak title+author genre classifier intended for rough corpus segmentation, triage, and candidate labeling of raw book libraries.
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