Instructions to use AyoubChLin/ESG-Bert-cnn-ag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyoubChLin/ESG-Bert-cnn-ag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AyoubChLin/ESG-Bert-cnn-ag")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/ESG-Bert-cnn-ag") model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/ESG-Bert-cnn-ag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b24bd0976a7887b935a1ec0abb10af5fbc3e64232a36de58795f648b3fc2ce1f
- Size of remote file:
- 438 MB
- SHA256:
- 8ecc7575ab9da9e5b490bd2bd10ff2ec7dc193254add5783b7380e168465333e
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