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")# pip install -U transformers accelerate # 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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Use the code below to get started with the model.
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("sadickam/sdg-classification-bert")
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model = AutoModelForSequenceClassification.from_pretrained("sadickam/sdg-classification-bert")
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```
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Use the code below to get started with the model.
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("sadickam/sdg-classification-bert")
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model = AutoModelForSequenceClassification.from_pretrained("sadickam/sdg-classification-bert")
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```
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