Instructions to use ESGBERT/SocialBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ESGBERT/SocialBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ESGBERT/SocialBERT-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ESGBERT/SocialBERT-base") model = AutoModelForMaskedLM.from_pretrained("ESGBERT/SocialBERT-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be8ffa196f08174b7598e2c1313f2c4883fc143c55bbcc524dacd3dedb7dc0f8
- Size of remote file:
- 329 MB
- SHA256:
- e9eecfe6763ceafab916f94e5274d038b6d6778c722c3a27a3cb2a5925cab38c
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