Instructions to use devangb4/scikit-issues-multilabel-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devangb4/scikit-issues-multilabel-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devangb4/scikit-issues-multilabel-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devangb4/scikit-issues-multilabel-classification") model = AutoModelForSequenceClassification.from_pretrained("devangb4/scikit-issues-multilabel-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload RobertaForSequenceClassification
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Upload DistilBertForSequenceClassification
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initial commit
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