Fill-Mask
Transformers
Safetensors
English
modernbert
finance
financial-nlp
domain-adaptation
dapt
masked-lm
Instructions to use BatuhanECB/FinModernBERT-large-DAPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BatuhanECB/FinModernBERT-large-DAPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BatuhanECB/FinModernBERT-large-DAPT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BatuhanECB/FinModernBERT-large-DAPT") model = AutoModelForMaskedLM.from_pretrained("BatuhanECB/FinModernBERT-large-DAPT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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docs: add official FinMTEB leaderboard placement of final embed model
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Card: link the released SEC-synthetic pairs dataset
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Card: rename to -v1 naming, cross-links updated
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FinModernBERT-large-DAPT: 5.65B-token finance MLM domain adaptation of ModernBERT-large
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initial commit
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