Instructions to use nbroad/ESG-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/ESG-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nbroad/ESG-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nbroad/ESG-BERT") model = AutoModelForSequenceClassification.from_pretrained("nbroad/ESG-BERT") - Notebooks
- Google Colab
- Kaggle
Model Training Data: Details on Sustainability Text Corpora.
#15
by pinpss - opened
Sorry to bother. In the Medium article, you mentioned that the training data comes from large unstructured sustainability text corpora, including sustainability reports and financial news articles, etc.
Could you please provide more details on the sources and the date range of the training data (from 2010 to 2020)? How were these sources selected?
pinpss changed discussion title from Details on Sustainability Text Corpora. to Model Training Data: Details on Sustainability Text Corpora.