Instructions to use yusufizzetmurat/finbert-fed-adjacent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yusufizzetmurat/finbert-fed-adjacent with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("yusufizzetmurat/finbert-fed-adjacent") model = AutoModelForPreTraining.from_pretrained("yusufizzetmurat/finbert-fed-adjacent") - Notebooks
- Google Colab
- Kaggle
yusufizzetmurat/finbert-fed-adjacent
Artefact for the fed-pulse FOMC text analytics project.
- Source code: https://github.com/yusufizzetmurat/fed-pulse
- Live demo: https://fedpulse.yusufizzetmurat.com
- License:
cc-by-4.0
Training corpus
FinBERT base + cross-bank pretraining substrate (samchain/BIS_speeches_97_23_MLM plus the gtfintechlab ECB / BoJ / BoE / BoC / RBA monetary-policy corpora reformatted as NSP pairs).
Training command
python -m app.data.continued_pretraining --substrate xbank_dapt --seed 11
Attribution
- Base model: ProsusAI/finbert (Araci, 2019).
- BIS speeches NSP pairs: samchain/BIS_speeches_97_23_MLM, redistributed from the Bank for International Settlements speeches archive.
- Cross-bank monetary-policy corpora: gtfintechlab multi-axis sentence datasets for the ECB, Bank of Japan, Bank of England, Bank of Canada, and Reserve Bank of Australia.
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