Text Classification
Transformers
PyTorch
English
bert
financial-text-analysis
esg
environmental-social-corporate-governance
Instructions to use yiyanghkust/finbert-esg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiyanghkust/finbert-esg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yiyanghkust/finbert-esg")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yiyanghkust/finbert-esg") model = AutoModelForSequenceClassification.from_pretrained("yiyanghkust/finbert-esg", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 536654271df5c4711ecd4fe5ff94b62162ae7d7f7192ae7057ee71baf4408183
- Size of remote file:
- 2.16 kB
- SHA256:
- 9652e1b966c866165f96db72faf24fabf036d3f88a13667eefa7010acd563c2e
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