Instructions to use yashcse21/text2sql-llama1b-adapters-caution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use yashcse21/text2sql-llama1b-adapters-caution with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download yashcse21/text2sql-llama1b-adapters-caution --local-dir text2sql-llama1b-adapters-caution
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from yashcse21/text2sql-llama1b-adapters-caution: direct link, hf CLI and curl.
- Browser
- Download file 723 Bytes
-
https://huggingface.co/yashcse21/text2sql-llama1b-adapters-caution/resolve/main/README.md
- Command line
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hf download hf://yashcse21/text2sql-llama1b-adapters-caution/README.md
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curl -L -o README.md https://huggingface.co/yashcse21/text2sql-llama1b-adapters-caution/resolve/main/README.md
723 Bytes
metadata
license: llama3.2
base_model: mlx-community/Llama-3.2-1B-Instruct-bf16
tags:
- text-to-sql
- lora
- mlx
- reasoning
library_name: mlx
Text-to-SQL · adapters_caution
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.