PEFT
Safetensors
Russian
qwen2
legal
contract-extraction
information-extraction
json-generation
lora
qwen
russian
enterprise
Instructions to use zieglerd/RussianConcsExt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zieglerd/RussianConcsExt with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-32B-Instruct") model = PeftModel.from_pretrained(base_model, "zieglerd/RussianConcsExt") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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Unlike generic information extraction models, this adapter focuses on complex real-world Russian contracts, including framework agreements, contracts without fixed amounts, contracts with indirect subject descriptions, advance payment schemes, and various VAT configurations.
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- **Developed by:** Dmitry Ziegler (Lead), Denis Karpov (
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- **Model type:** LoRA Adapter
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- **Language(s):** Russian
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- **License:** Apache-2.0 (inherits base model license)
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Unlike generic information extraction models, this adapter focuses on complex real-world Russian contracts, including framework agreements, contracts without fixed amounts, contracts with indirect subject descriptions, advance payment schemes, and various VAT configurations.
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- **Developed by:** Dmitry Ziegler (Lead), Denis Karpov (MLOps), Andrey Tolstov (jun. MLOps)
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- **Model type:** LoRA Adapter
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- **Language(s):** Russian
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- **License:** Apache-2.0 (inherits base model license)
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