SocialBERT social EU AI Act Compliance Profile

Model Card for SocialBERT-social

Model Description

Based on this paper, this is the SocialBERT-social language model. A language model that is trained to better classify social texts in the ESG domain.

Using the SocialBERT-base model as a starting point, the SocialBERT-social Language Model is additionally fine-trained on a 2k social dataset to detect social text samples.

How to Get Started With the Model

See these tutorials on Medium for a guide on model usage, large-scale analysis, and fine-tuning.

You can use the model with a pipeline for text classification:

from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

tokenizer_name = "ESGBERT/SocialBERT-social"
model_name = "ESGBERT/SocialBERT-social"
 
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, max_len=512)
 
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer) # set device=0 to use GPU
 
# See https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline
print(pipe("We follow rigorous supplier checks to prevent slavery and ensure workers' rights.", padding=True, truncation=True))

More details can be found in the paper

@article{schimans

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