Instructions to use gggff123/Webqwen-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use gggff123/Webqwen-0.5b 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 gggff123/Webqwen-0.5b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf gggff123/Webqwen-0.5b:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf gggff123/Webqwen-0.5b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf gggff123/Webqwen-0.5b:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf gggff123/Webqwen-0.5b:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf gggff123/Webqwen-0.5b:Q4_K_M

Use Docker

docker model run hf.co/gggff123/Webqwen-0.5b:Q4_K_M

Llama new
LM Studio
Jan
Ollama
How to use gggff123/Webqwen-0.5b with Ollama:
```
ollama run hf.co/gggff123/Webqwen-0.5b:Q4_K_M
```
Unsloth Desktop

How to use gggff123/Webqwen-0.5b with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gggff123/Webqwen-0.5b: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": "gggff123/Webqwen-0.5b:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use gggff123/Webqwen-0.5b with Docker Model Runner:
```
docker model run hf.co/gggff123/Webqwen-0.5b:Q4_K_M
```

Lemonade

How to use gggff123/Webqwen-0.5b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gggff123/Webqwen-0.5b:Q4_K_M

Run and chat with the model

lemonade run user.Webqwen-0.5b-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use gggff123/Webqwen-0.5b with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gggff123/Webqwen-0.5b: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 gggff123/Webqwen-0.5b:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use gggff123/Webqwen-0.5b with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf gggff123/Webqwen-0.5b: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 "gggff123/Webqwen-0.5b: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"

Webqwen-0.5b : GGUF

A model designed for web & html generation mainly focuses on the ui. while the original qwen model does not apply any css , webqwen can generate html designs like those of gpt 4o or gpt 3.5 . while remaining at a relatively smaller size.

How it was made

trained in unsloth studio (T4 colab)
Lora | Epoch = 1
forgot dataset name.

Example usage:

For text only LLMs: llama-cli -hf gggff123/Webqwen-0.5b --jinja
For multimodal models: llama-mtmd-cli -hf gggff123/Webqwen-0.5b --jinja

Available model files:

Qwen2.5-0.5B-Instruct.Q4_K_M.gguf
Qwen2.5-0.5B-Instruct.Q5_K_M.gguf

feel free to try it out!

Downloads last month: 243

GGUF

Model size

0.5B params

Architecture

qwen2

Hardware compatibility

4-bit

5-bit

Inference Providers NEW

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Model tree for gggff123/Webqwen-0.5b

Base model

Qwen/Qwen2.5-0.5B

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Qwen/Qwen2.5-0.5B-Instruct

Quantized

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