Instructions to use edereynal/financial_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edereynal/financial_bert with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("edereynal/financial_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add paper.pdf, expand benchmarks to 65/67 entries, add MLM-pretrained model
- Added paper.pdf to repo - Expanded numeracy test from 29 to 65 ordering groups - Expanded retrieval test from 20 to 67 query-match pairs - Added MLM-pretrained checkpoint as 5th benchmark model - Updated benchmark output formatting for 5-model comparison Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>4aa1290
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Adding numeracy ordering test results
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>f33e554
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Updating benchmarks
560a36a -
Updating gitignore
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Adding a few other things
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Updated model card
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Adding a small test to illustrrate
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Benchmarks
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Update README with checkpoint loading instructions
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Add CLS encoder weights (T5-style training, epoch 5)
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Add MLM pretrained weights (epoch 3)
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Add model card metadata
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Initial commit: FinancialModernBERT package
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initial commit
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