Instructions to use mervp/SQLGenie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mervp/SQLGenie with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "mervp/SQLGenie") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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README.md
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- Produce invalid SQL for a very few edge cases
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- Infer incorrect table or column names not present in prompt
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- Assume a generic SQL dialect (closer to MySQL/PostgreSQL Databases)
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### Recommendations
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If this model helped you, please consider leaving a 👍 like. Your support helps this model reach more developers and encourages further improvements if any.
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## How to Get Started with the Model
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- Produce invalid SQL for a very few edge cases
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- Infer incorrect table or column names not present in prompt
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- Assume a generic SQL dialect (closer to MySQL/PostgreSQL Databases)
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### Recommendations
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- Always validate and test generated queries before execution in a production database.
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## How to Get Started with the Model
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