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
| { | |
| "distance_matrix": { | |
| "Literary / General Fiction": { | |
| "Romance": 0.25, | |
| "Mystery / Thriller / Crime": 0.25, | |
| "Sci-Fi / Fantasy": 0.25, | |
| "Nonfiction": 0.60 | |
| }, | |
| "Romance": { | |
| "Mystery / Thriller / Crime": 0.25, | |
| "Sci-Fi / Fantasy": 0.40, | |
| "Nonfiction": 0.75 | |
| }, | |
| "Sci-Fi / Fantasy": { | |
| "Mystery / Thriller / Crime": 0.40, | |
| "Nonfiction": 0.75 | |
| }, | |
| "Mystery / Thriller / Crime": { | |
| "Nonfiction": 0.75 | |
| } | |
| }, | |
| "exact_auto_label": { | |
| "min_top1_confidence": 0.80, | |
| "min_margin": 0.15 | |
| }, | |
| "ambiguous_bucket": { | |
| "min_top1_confidence": 0.50, | |
| "max_top1_confidence": 0.80, | |
| "max_margin": 0.20, | |
| "max_top1_top2_distance": 0.25 | |
| } | |
| } | |