Instructions to use albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5") model = PeftModel.from_pretrained(base_model, "albertkingdom/deepseek-coder-7b-text2sql-magicoder-lora") - Notebooks
- Google Colab
- Kaggle
Commit History
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Replace with SQL+Magicoder mixed-training adapter (better SQL generalization + retained code capability, see experiment_log.md)
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Update adapter: mix Magicoder code data (30% SQL / 70% code) to mitigate code-capability degradation
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Add LoRA adapter
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initial commit
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