Instructions to use ab3223323/esgBERTv1_Access_to_Finance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ab3223323/esgBERTv1_Access_to_Finance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ab3223323/esgBERTv1_Access_to_Finance")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ab3223323/esgBERTv1_Access_to_Finance") model = AutoModelForSequenceClassification.from_pretrained("ab3223323/esgBERTv1_Access_to_Finance") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b439d5d9326bee1b4083cd2c96b0bfe313b0aedb87ba58cfadf330e0c80de193
- Size of remote file:
- 876 MB
- SHA256:
- 2961e49f1495895a8a28c9ab905b4ca443d12b70bef7708810b7374249c7ac66
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