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
Related text to the predicted entity
#4
by ElKe5a - opened
Hello @ElKe5a
It is possible to extract the text reference for the prediction. You can do that using the SHAP python package. Please have a look at the SHAP documentation. It has a specific function for explaining the predictions of NLP models with very helpful visualisations.
Hopefully, this helps. If you need further information please do let me know.
Regards
Sadick
sadickam changed discussion status to closed