Instructions to use mrcmilo/phi3-text2sql-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrcmilo/phi3-text2sql-lora with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mrcmilo/phi3-text2sql-lora",
	filename="phi-3-mini-4k-instruct.Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use mrcmilo/phi3-text2sql-lora with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mrcmilo/phi3-text2sql-lora:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mrcmilo/phi3-text2sql-lora:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf mrcmilo/phi3-text2sql-lora:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf mrcmilo/phi3-text2sql-lora:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf mrcmilo/phi3-text2sql-lora:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mrcmilo/phi3-text2sql-lora:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf mrcmilo/phi3-text2sql-lora:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mrcmilo/phi3-text2sql-lora:Q4_K_M

Use Docker

docker model run hf.co/mrcmilo/phi3-text2sql-lora:Q4_K_M

LM Studio
Jan
Ollama
How to use mrcmilo/phi3-text2sql-lora with Ollama:
```
ollama run hf.co/mrcmilo/phi3-text2sql-lora:Q4_K_M
```

Unsloth Studio new

How to use mrcmilo/phi3-text2sql-lora with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mrcmilo/phi3-text2sql-lora to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mrcmilo/phi3-text2sql-lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mrcmilo/phi3-text2sql-lora to start chatting

Docker Model Runner
How to use mrcmilo/phi3-text2sql-lora with Docker Model Runner:
```
docker model run hf.co/mrcmilo/phi3-text2sql-lora:Q4_K_M
```

Lemonade

How to use mrcmilo/phi3-text2sql-lora with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mrcmilo/phi3-text2sql-lora:Q4_K_M

Run and chat with the model

lemonade run user.phi3-text2sql-lora-Q4_K_M

List all available models

lemonade list

This is a specialized Text-to-SQL model fine-tuned from the Microsoft Phi-3-mini-4k-instruct architecture. It has been optimized using Unsloth to provide high-accuracy SQL generation while remaining lightweight enough to run on consumer hardware.

Key Features

Architecture: Phi-3-mini (3.8B parameters)
Quantization: Q4_K_M GGUF & Q5_K_M
Training Technique: Fine-tuned using Lora with Unsloth.
Format: GGUF (Ready for Ollama, LM Studio, and llama.cpp)
- phi-3-mini-4k-instruct.Q4_K_M.gguf
- phi-3-mini-4k-instruct.Q5_K.gguf

Usage Instructions

Ollama (Recommended)

To deploy locally:

Download the .gguf file (Q4 or Q5).
Create the Modelfile with the following instructions

FROM ./phi-3-mini-4k-instruct.Q4_K_M.gguf

TEMPLATE """<s><|user|>
Schema: {{ .System }}
Question: {{ .Prompt }}<|end|>
<|assistant|>
"""

# Parameters for SQL stability
PARAMETER stop "<|end|>"
PARAMETER stop "<s>"
PARAMETER stop "</s>"
PARAMETER temperature 0.0

Run ollama create phi3-sql-expert -f Modelfile
Run ollama run phi3-sql-expert "schema: CREATE TABLE table_name_7 (nba_draft VARCHAR, school VARCHAR) question: What was the NBA draft status for Northeast High School?"
The answer should be SELECT nba_draft FROM table_name_7 WHERE school = "Northeast"

Evaluation Data

The model was fine-tuned on the sql-create-context dataset, focusing on:

Mapping natural language to SQL queries with SELECT, WHERE, and JOIN statements.
Understanding table schemas provided in the prompt.
Maintaining strict SQL syntax in the response.

Recommended Settings

Temperature: 0.0 or 0.1 (SQL requires deterministic output).

Stop Tokens: Ensure <|end|> is set as a stop sequence to prevent "infinite looping" generation.

Context Window: 2048 tokens.

Model Developer: msquared

Base Model: Phi-3-mini-4k-instruct

Downloads last month: 3

GGUF

Model size

4B params

Architecture

llama

Hardware compatibility

4-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for mrcmilo/phi3-text2sql-lora

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