Instructions to use nbroad/ESG-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/ESG-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nbroad/ESG-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nbroad/ESG-BERT") model = AutoModelForSequenceClassification.from_pretrained("nbroad/ESG-BERT") - Inference
- Notebooks
- Google Colab
- Kaggle
updates authors
Browse files
README.md
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- **Developed by:** [Charan Pothireddi](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/) and [Parabole.ai](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/)
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- **Shared by [Optional]:** HuggingFace
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- **Model type:** Language model
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- **Language(s) (NLP):** en
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More information needed
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# Model Card Authors [optional]
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[Charan Pothireddi](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/) and [Parabole.ai](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/), in collaboration with the Ezi Ozoani and the HuggingFace Team
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# Model Card Contact
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- **Developed by:** [Mukut Mukherjee](https://www.linkedin.com/in/mukutm/), [Charan Pothireddi](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/) and [Parabole.ai](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/)
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- **Shared by [Optional]:** HuggingFace
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- **Model type:** Language model
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- **Language(s) (NLP):** en
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More information needed
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# Model Card Authors [optional]
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[Mukut Mukherjee](https://www.linkedin.com/in/mukutm/), [Charan Pothireddi](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/) and [Parabole.ai](https://www.linkedin.com/in/sree-charan-pothireddi-6a0a3587/), in collaboration with the Ezi Ozoani and the HuggingFace Team
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# Model Card Contact
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