Instructions to use sadickam/sdgBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sadickam/sdgBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sadickam/sdgBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sadickam/sdgBERT") model = AutoModelForSequenceClassification.from_pretrained("sadickam/sdgBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Model Sources
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- **Repository:** https://huggingface.co/sadickam/sdg-classification-bert
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- **Demo
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### Direct Use
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### Model Sources
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- **Repository:** https://huggingface.co/sadickam/sdg-classification-bert
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- **Demo:** option 1 (copy/past text and csv): https://sadickam-sdg-text-classifier.hf.space/; option 2 (PDF documents): https://sadickam-document-sdg-app-cpu.hf.space
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### Direct Use
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