Instructions to use junmingg/qwen2.5-coder-7b-text2sql-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 junmingg/qwen2.5-coder-7b-text2sql-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 junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF: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 junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF: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 junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Use Docker

docker model run hf.co/junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "junmingg/qwen2.5-coder-7b-text2sql-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "junmingg/qwen2.5-coder-7b-text2sql-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Ollama
How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with Ollama:
```
ollama run hf.co/junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
```
Unsloth Desktop

How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with Docker Model Runner:
```
docker model run hf.co/junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
```

Lemonade

How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.qwen2.5-coder-7b-text2sql-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use junmingg/qwen2.5-coder-7b-text2sql-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

junmingg commited on Jun 30

Commit

7382216

verified ·

1 Parent(s): 311d4b7

Add README

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README.md +23 -42

README.md CHANGED Viewed

@@ -1,42 +1,23 @@
----
-license: apache-2.0
-base_model: junmingg/qwen2.5-coder-7b-text2sql
-datasets:
-  - b-mc2/sql-create-context
-pipeline_tag: text-generation
-tags:
-  - text-to-sql
-  - gguf
-  - llama.cpp
-  - ollama
-  - qwen2.5
----
-# Qwen2.5-Coder-7B Text-to-SQL — GGUF quants
-GGUF quantizations of [`junmingg/qwen2.5-coder-7b-text2sql`](https://huggingface.co/junmingg/qwen2.5-coder-7b-text2sql)
-for CPU/GPU inference via [llama.cpp](https://github.com/ggerganov/llama.cpp), [Ollama](https://ollama.com),
-LM Studio, etc.
-| File | Quant | Size | Notes |
-|---|---|---|---|
-| `qwen2.5-coder-7b-instruct.Q4_K_M.gguf` | Q4_K_M | ~4.7 GB | 4-bit, best size/quality balance (recommended) |
-| `qwen2.5-coder-7b-instruct.Q8_0.gguf` | Q8_0 | ~8.1 GB | 8-bit, near-lossless |
-See the [main model card](https://huggingface.co/junmingg/qwen2.5-coder-7b-text2sql) for results
-(exact 78.8% / semantic 86.2% / validity 99.2% vs base 3.8 / 67.0 / 100), training details, and the
-**required system prompt** — the model expects the text-to-SQL system message + ChatML format.
-## Quick start (Ollama)
-```bash
-ollama run hf.co/junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
-```
-## Quick start (llama.cpp)
-```bash
-llama-cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF:Q4_K_M
-```
-License: Apache-2.0 (base model) / data CC-BY-4.0.

+---
+tags:
+- gguf
+- llama.cpp
+- unsloth
+---
+# qwen2.5-coder-7b-text2sql-GGUF : GGUF
+This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
+**Example usage**:
+- For text only LLMs:    `llama-cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF --jinja`
+- For multimodal models: `llama-mtmd-cli -hf junmingg/qwen2.5-coder-7b-text2sql-GGUF --jinja`
+## Available Model files:
+- `qwen2.5-coder-7b-instruct.Q6_K.gguf`
+## Ollama
+An Ollama Modelfile is included for easy deployment.
+This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)