Instructions to use yanlanh/subject-clf-deberta-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yanlanh/subject-clf-deberta-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yanlanh/subject-clf-deberta-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yanlanh/subject-clf-deberta-v3") model = AutoModelForSequenceClassification.from_pretrained("yanlanh/subject-clf-deberta-v3") - Notebooks
- Google Colab
- Kaggle
subject-clf-deberta-v3
Multi-label subject classifier -- labels: English, Maths, Science, Civics, Geology.
- base:
microsoft/deberta-v3-base - trained on
yanlanh/multilabel-subject-dataset@5d8dc42
from transformers import AutoModelForSequenceClassification, AutoTokenizer
tok = AutoTokenizer.from_pretrained("yanlanh/subject-clf-deberta-v3")
model = AutoModelForSequenceClassification.from_pretrained("yanlanh/subject-clf-deberta-v3")
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