Instructions to use chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

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 chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

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 chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

Use Docker

docker model run hf.co/chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

LM Studio
Jan
Ollama
How to use chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF with Ollama:
```
ollama run hf.co/chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
```
Unsloth Desktop
Docker Model Runner
How to use chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF with Docker Model Runner:
```
docker model run hf.co/chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16
```

Lemonade

How to use chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF:F16

Run and chat with the model

lemonade run user.gemma-3-270m-text2sql-oracle-postgres-GGUF-F16

List all available models

lemonade list

Atomic Chat

gemma-3-270m-text2sql-oracle-postgres-GGUF / README.md

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	---
	base_model: chabab/gemma-3-270m-text2sql-oracle-postgres
	tags: [gguf, text-to-sql, sql, oracle, postgresql, gemma3]
	license: apache-2.0
	---

	# gemma-3-270m-text2sql-oracle-postgres-GGUF

	GGUF builds of [`chabab/gemma-3-270m-text2sql-oracle-postgres`](https://huggingface.co/chabab/gemma-3-270m-text2sql-oracle-postgres) — Gemma-3 270M fine-tuned for
	Oracle / PostgreSQL text-to-SQL.

	\| File \| Quant \| Size \|
	\|---\|---\|---\|
	\| `gemma-3-270m-text2sql-f16.gguf` \| f16 \| 543 MB \|
	\| `gemma-3-270m-text2sql-q8_0.gguf` \| q8_0 \| 292 MB \|

	## Ollama

	```bash
	huggingface-cli download chabab/gemma-3-270m-text2sql-oracle-postgres-GGUF gemma-3-270m-text2sql-q8_0.gguf Modelfile --local-dir .
	ollama create text2sql -f Modelfile
	ollama run text2sql "Schema:
	employees(employee_id INTEGER PK, first_name VARCHAR(50), last_name VARCHAR(50), salary NUMERIC(12,2))

	Question:
	Show the five employees with the largest salary. Return only the SQL."
	```

	## llama.cpp

	```bash
	llama-cli -m gemma-3-270m-text2sql-q8_0.gguf --temp 0 -p "<your schema + question>"
	```

	Use greedy decoding (`temperature 0`). The model is trained to emit exactly one SQL
	statement with no fences or commentary.