Instructions to use yarenty/qwen2.5-3B-datafusion-instruct-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 yarenty/qwen2.5-3B-datafusion-instruct-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 yarenty/qwen2.5-3B-datafusion-instruct-gguf
# Run inference directly in the terminal:
llama cli -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf
# Run inference directly in the terminal:
llama cli -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

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 yarenty/qwen2.5-3B-datafusion-instruct-gguf
# Run inference directly in the terminal:
./llama-cli -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

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 yarenty/qwen2.5-3B-datafusion-instruct-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

Use Docker

docker model run hf.co/yarenty/qwen2.5-3B-datafusion-instruct-gguf

LM Studio
Jan
Ollama
How to use yarenty/qwen2.5-3B-datafusion-instruct-gguf with Ollama:
```
ollama run hf.co/yarenty/qwen2.5-3B-datafusion-instruct-gguf
```
Unsloth Desktop

How to use yarenty/qwen2.5-3B-datafusion-instruct-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

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": "yarenty/qwen2.5-3B-datafusion-instruct-gguf"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use yarenty/qwen2.5-3B-datafusion-instruct-gguf with Docker Model Runner:
```
docker model run hf.co/yarenty/qwen2.5-3B-datafusion-instruct-gguf
```

Lemonade

How to use yarenty/qwen2.5-3B-datafusion-instruct-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull yarenty/qwen2.5-3B-datafusion-instruct-gguf

Run and chat with the model

lemonade run user.qwen2.5-3B-datafusion-instruct-gguf-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use yarenty/qwen2.5-3B-datafusion-instruct-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 yarenty/qwen2.5-3B-datafusion-instruct-gguf

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 yarenty/qwen2.5-3B-datafusion-instruct-gguf

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use yarenty/qwen2.5-3B-datafusion-instruct-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf yarenty/qwen2.5-3B-datafusion-instruct-gguf

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 "yarenty/qwen2.5-3B-datafusion-instruct-gguf" \
  --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"

yarenty commited on Aug 11, 2025

Commit

1b060fd

verified ·

1 Parent(s): b36d0ba

Update README.md

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README.md +5 -44

README.md CHANGED Viewed

@@ -134,49 +134,17 @@ You are a helpful, concise, and accurate coding assistant specialized in Rust an
 - **Response Time:** Fast generation with proper stop sequences
 - **Memory Usage:** Efficient token management
-## Use Cases
-### Development
-- **Code Generation:** Generate Rust functions and DataFusion queries
-- **Debugging:** Identify and fix common issues
-- **Documentation:** Create clear technical explanations
-- **Testing:** Generate test cases and validation code
-### Learning
-- **Tutorial Creation:** Step-by-step learning materials
-- **Best Practices:** Learn recommended approaches
-- **Pattern Recognition:** Understand common design patterns
-- **API Exploration:** Discover available functionality
-### Production Support
-- **Query Optimization:** Improve SQL performance
-- **Troubleshooting:** Resolve runtime issues
-- **Integration:** Connect different data sources
-- **Monitoring:** Set up observability and tracing
-## Limitations and Considerations
-### Technical Limitations
-- **Context Window:** Limited to training data scope
-- **Real-time Updates:** May not reflect latest API changes
-- **Complex Queries:** Very complex scenarios may require human review
-- **Edge Cases:** Unusual configurations may need manual intervention
-### Best Practices
-- **Verify Output:** Always review generated code before deployment
-- **Test Thoroughly:** Validate generated queries and functions
-- **Stay Updated:** Check for newer model versions
-- **Human Oversight:** Use as assistant, not replacement for expertise
 ## Installation and Setup
 ### Ollama (Recommended)
 ```bash
 # Pull the model
-ollama pull jaro/qwen2.5-3B-datafusion-instruct
 # Run inference
-ollama run jaro/qwen2.5-3B-datafusion-instruct
 ```
 ### Direct GGUF Usage
@@ -195,15 +163,8 @@ ollama run jaro/qwen2.5-3B-datafusion-instruct
 | **Deployment** | Development/Production | Production/Resource-constrained |
 | **Use Case** | Maximum quality | Balanced performance |
-## Community and Support
-### Contributing
-- Report issues with model behavior
-- Suggest improvements to training data
-- Share use cases and success stories
-- Contribute to the DataFusion ecosystem
-### Resources
 - **DataFusion Documentation:** https://docs.datafusion.org/
 - **Apache Arrow:** https://arrow.apache.org/
 - **Rust Programming Language:** https://www.rust-lang.org/
@@ -218,7 +179,7 @@ When using this model in research or publications, please cite:
   title={Qwen2.5-3B-DataFusion-Instruct: A Specialized Model for DataFusion Ecosystem},
   author={Fine-tuned on DataFusion Ecosystem QA Dataset},
   year={2025},
-  url={https://github.com/apache/datafusion},
   license={Apache-2.0}
 }
 ```

 - **Response Time:** Fast generation with proper stop sequences
 - **Memory Usage:** Efficient token management
 ## Installation and Setup
 ### Ollama (Recommended)
 ```bash
 # Pull the model
+ollama pull jaro/qwen_datafusion
 # Run inference
+ollama run jaro/qwen_datafusion
 ```
 ### Direct GGUF Usage
 | **Deployment** | Development/Production | Production/Resource-constrained |
 | **Use Case** | Maximum quality | Balanced performance |
+## Resources
 - **DataFusion Documentation:** https://docs.datafusion.org/
 - **Apache Arrow:** https://arrow.apache.org/
 - **Rust Programming Language:** https://www.rust-lang.org/
   title={Qwen2.5-3B-DataFusion-Instruct: A Specialized Model for DataFusion Ecosystem},
   author={Fine-tuned on DataFusion Ecosystem QA Dataset},
   year={2025},
+  url={https://github.com/yarenty/trainer},
   license={Apache-2.0}
 }
 ```