Instructions to use Jackett/subject_classifier_extended with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jackett/subject_classifier_extended with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jackett/subject_classifier_extended")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jackett/subject_classifier_extended") model = AutoModelForSequenceClassification.from_pretrained("Jackett/subject_classifier_extended") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Label mappings {'LABEL_0':'Biology','LABEL_1':'Physics','LABEL_2':'Chemistry','LABEL_3':'Maths','LABEL_4':'Social Science','LABEL_5':'English'}
Training data distribution Physics - 7000 Maths - 7000 Biology - 7000 Chemistry - 7000 English - 5254 Social Science - 7000
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