Instructions to use yashcse21/text2sql-llama1b-cot-lr2e-4-l8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use yashcse21/text2sql-llama1b-cot-lr2e-4-l8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir text2sql-llama1b-cot-lr2e-4-l8 yashcse21/text2sql-llama1b-cot-lr2e-4-l8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Text-to-SQL · cot_lr2e-4_L8
MLX LoRA adapter fine-tuned from
mlx-community/Llama-3.2-1B-Instruct-bf16 to turn a natural-language question + a CREATE TABLE schema into a
schema-faithful SQLite SELECT (reasoning models emit Reasoning: … / SQL: …).
# download the adapter, then:
from mlx_lm import load
model, tok = load("mlx-community/Llama-3.2-1B-Instruct-bf16", adapter_path="<downloaded-adapter-dir>")
Pair generation with a deterministic AST guardrail (single read-only SELECT). See the project repo for the data pipeline, study, and evaluation.
Hardware compatibility
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Model tree for yashcse21/text2sql-llama1b-cot-lr2e-4-l8
Base model
mlx-community/Llama-3.2-1B-Instruct-bf16