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:
- 81c9354a202bdc597691ae04c53cedc60185b859f273d30c2779fdcee895a849
- Size of remote file:
- 3.96 kB
- SHA256:
- 74601bdd1b03824aed48dfe092fd255da808edb6f77aecd9d1ce0eb153c3124c
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