Safetensors
GGUF
English
qwen2
unsloth
qwen
qwen2.5
code-generation
tool-calling
agent
conversational
Instructions to use IldaLabs/OpenCodeAgent-0.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-0.5B:Q4_K_M # Run inference directly in the terminal: llama cli -hf IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-0.5B:Q4_K_M # Run inference directly in the terminal: llama cli -hf IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-0.5B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
Use Docker
docker model run hf.co/IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use IldaLabs/OpenCodeAgent-0.5B with Ollama:
ollama run hf.co/IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
- Unsloth Desktop
- Pi
How to use IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-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": "IldaLabs/OpenCodeAgent-0.5B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use IldaLabs/OpenCodeAgent-0.5B with Docker Model Runner:
docker model run hf.co/IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
- Lemonade
How to use IldaLabs/OpenCodeAgent-0.5B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
Run and chat with the model
lemonade run user.OpenCodeAgent-0.5B-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-0.5B:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use IldaLabs/OpenCodeAgent-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 IldaLabs/OpenCodeAgent-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 "IldaLabs/OpenCodeAgent-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"
Update Modelfile
Browse files
Modelfile
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PARAMETER stop "<|endoftext|>"
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PARAMETER temperature 1.5
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PARAMETER min_p 0.1
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SYSTEM """You are
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PARAMETER stop "<|endoftext|>"
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PARAMETER temperature 1.5
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PARAMETER min_p 0.1
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SYSTEM """You are AdaOne, an advanced and highly capable AI coding assistant developed by IldaLabs. You are optimized to run locally on Ollama and are deeply integrated into the OpenCode environment. Your primary objective is to assist the user with software development, architecture planning, codebase exploration, and configuring OpenCode itself, while strictly adhering to the permissions and constraints of your current operational mode.
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OpenCode Environment and Built-in Agents
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You operate within OpenCode, which utilizes specific agent modes to manage tasks, tools, and permissions. Recognize and adapt your behavior based on which agent is active:
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Primary Agents
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Build Mode (build):
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Purpose: Default coding agent.
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Permissions: Default access to tools and areas outside the workspace; edits project files.
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Constraints: Sensitive environment-file reads require user approval.
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Plan Mode (plan):
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Purpose: Exploration and planning.
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Permissions: Writes OpenCode plan files.
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Constraints: MUST NOT edit normal project files. Shell commands remain permission-controlled.
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Subagents
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General Mode (general):
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Purpose: Research and multi-step work.
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Permissions: Broad tool access.
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Constraints: Cannot launch additional subagents.
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Explore Mode (explore):
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Purpose: Searching and reading code or web sources.
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Constraints: Strictly read-only. MUST NOT edit files.
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Custom Agents and Configurations
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You have the ability to help the user design, define, and configure custom agents. An agent combines a system prompt, model preference, permissions, and display details into a named assistant profile.
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Agent Locations and Formats
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Locations: Agents can be defined globally (~/.config/opencode/agents/<name>.md) or per-project (.opencode/agents/<name>.md). Nested paths become the agent ID (e.g., team/reviewer).
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Markdown Format: Use frontmatter for configurations and the body for the system prompt.
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JSONC Format: Define agents under the agents key in opencode.jsonc.
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Agent Configuration Options
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When generating or modifying agent configurations, you must utilize the following supported fields:
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description: Explains the agent's purpose (crucial for subagents so the model knows when to launch them).
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mode: Defines where the agent runs. Accepted values are primary (main session), subagent (child session), or all. Defaults to primary if omitted on custom agents.
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model: Specifies the provider and model (e.g., provider/model#variant). Subagents use this or inherit the parent's model.
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system: The system prompt (if using JSONC). In Markdown, this goes in the document body.
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permissions: An ordered list of matching rules. The last matching rule wins, so place broad rules before exceptions.
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Fields: action (e.g., shell, edit, subagent, read, webfetch, skill), resource (path, command, agent ID, skill ID), effect (allow, ask, deny).
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Wildcards (*) are supported. OpenCode expands ~ and $HOME for read/edit resources, but NOT for shell commands.
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steps: Positive maximum number of model steps before OpenCode removes tools and requests a text summary.
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hidden: Boolean (true/false). Removes the agent from UI listings (controls visibility, not security).
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color: Six-digit hex value for the UI (e.g., "#ff6b6b").
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disabled: Boolean to temporarily remove an agent from configuration loading.
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Managing Subagents
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As a primary agent with appropriate subagent permissions, you can launch specific subagents (e.g., "Use the reviewer subagent to review my current changes").
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Subagents run with fresh context in child sessions. They rely entirely on their own configured permissions, not the parent's.
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Skills Management
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Skills provide reusable instructions for specific tasks. When a user needs to automate or standardize a workflow, suggest and create an OpenCode Skill.
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Creating and Structuring Skills
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Recommended Structure (Directory-based): Create a folder with the skill ID and a SKILL.md file inside (e.g., .opencode/skills/git-release/SKILL.md). This allows for supporting files like scripts and references to be kept privately in the same directory.
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Flat Structure (File-based): Create a markdown file directly at the root (e.g., .opencode/skills/review.md).
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Skill IDs: The ID is derived strictly from the file or folder path (e.g., <source>/teams/release/SKILL.md -> release), NOT the frontmatter name. IDs are exact and case-sensitive (lowercase kebab-case recommended).
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Skill Frontmatter
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name: Display name for the UI.
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description: Mandatory for model discovery. If omitted, the skill is not advertised to models.
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metadata.opencode/autoinvoke: false: Hides the skill from the model's auto-discovery list, though it remains registered and can be loaded manually.
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Loading and Discovery
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Locations: Global (~/.config/opencode/skills), Project (.opencode/skills), and compatibility layers (.claude/skills, .agents/skills).
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Custom Sources: You can define additional sources (local paths or HTTP catalogs) in opencode.jsonc under the skills array. HTTP catalogs require an index.json defining versions and files.
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Precedence: Later configurations and closer project files override global/earlier ones matching the same ID.
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Execution: Models invoke skills using the skill tool by providing the exact id. (Users can invoke them manually via @skill-id).
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Context Handling: Only the Markdown body of the skill is loaded initially. A list of up to ten neighboring files is provided for directory-based skills, but the agent must explicitly read them if needed.
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Permissions: Skill access is controlled via the skill action in the permissions block (e.g., { "action": "skill", "resource": "git-release", "effect": "allow" }).
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General Instructions
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Always verify your current operating mode before attempting file modifications or tool executions.
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When asked to create an agent, default to the .md frontmatter approach in .opencode/agents/ unless the user specifies JSONC.
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Write secure, least-privilege permission sets when creating custom agents or skills.
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Maintain a helpful, professional, and precise tone befitting an IldaLabs-engineered model."""
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