Instructions to use SuNavar/Pygenesis_ResolveExpert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use SuNavar/Pygenesis_ResolveExpert 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 SuNavar/Pygenesis_ResolveExpert
# Run inference directly in the terminal:
llama cli -hf SuNavar/Pygenesis_ResolveExpert

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SuNavar/Pygenesis_ResolveExpert
# Run inference directly in the terminal:
llama cli -hf SuNavar/Pygenesis_ResolveExpert

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 SuNavar/Pygenesis_ResolveExpert
# Run inference directly in the terminal:
./llama-cli -hf SuNavar/Pygenesis_ResolveExpert

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 SuNavar/Pygenesis_ResolveExpert
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SuNavar/Pygenesis_ResolveExpert

Use Docker

docker model run hf.co/SuNavar/Pygenesis_ResolveExpert

Llama new
LM Studio
Jan

vLLM

How to use SuNavar/Pygenesis_ResolveExpert with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/SuNavar/Pygenesis_ResolveExpert

Ollama
How to use SuNavar/Pygenesis_ResolveExpert with Ollama:
```
ollama run hf.co/SuNavar/Pygenesis_ResolveExpert
```
Unsloth Desktop

How to use SuNavar/Pygenesis_ResolveExpert with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SuNavar/Pygenesis_ResolveExpert

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": "SuNavar/Pygenesis_ResolveExpert"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use SuNavar/Pygenesis_ResolveExpert with Docker Model Runner:
```
docker model run hf.co/SuNavar/Pygenesis_ResolveExpert
```

Lemonade

How to use SuNavar/Pygenesis_ResolveExpert with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SuNavar/Pygenesis_ResolveExpert

Run and chat with the model

lemonade run user.Pygenesis_ResolveExpert-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use SuNavar/Pygenesis_ResolveExpert with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SuNavar/Pygenesis_ResolveExpert

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 SuNavar/Pygenesis_ResolveExpert

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use SuNavar/Pygenesis_ResolveExpert with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SuNavar/Pygenesis_ResolveExpert

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 "SuNavar/Pygenesis_ResolveExpert" \
  --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"

SuNavar commited on Jul 18

Commit

e4331f1

verified ·

1 Parent(s): 28d0ceb

Update README.md

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README.md +98 -5

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@@ -1,14 +1,107 @@
 ---
-license: apache-2.0
 language:
 - en
-- es
-base_model:
-- Qwen/Qwen2.5-7B-Instruct
 pipeline_tag: text-generation
 tags:
 - davinci-resolve
 - video-editing
 - local-inference
 - gguf
-    ---

 ---
 language:
 - en
+license: apache-2.0
 pipeline_tag: text-generation
+library_name: llama-cpp
 tags:
 - davinci-resolve
 - video-editing
 - local-inference
 - gguf
+- qwen
+base_model: Qwen/Qwen2.5-7B-Instruct
+---
+# Pygenesis ResolveExpert
+Pygenesis ResolveExpert is a task-oriented assistant model for **DaVinci Resolve** workflows (Edit, Color, Fusion, Fairlight, Deliver), packaged for local inference as GGUF.
+## Model Overview
+`pygenesis-resolve-q4km.gguf` is a quantized local-inference variant of a Resolve-focused fine-tuned model.
+Main goals:
+- Provide practical, step-by-step help for real editing and post-production tasks.
+- Keep latency reasonable on desktop hardware.
+- Run fully on-device with no cloud dependency.
+## Studio vs Free: Context Behavior
+The model is the same in both editions.
+The key difference is **how runtime context is provided**.
+### DaVinci Resolve Studio (Integrated Plugin)
+In Studio, the Workflow Integration plugin can automatically read and pass context such as:
+- Current Resolve page (`Media`, `Cut`, `Edit`, `Fusion`, `Color`, `Fairlight`, `Deliver`)
+- Current project and timeline names
+- Basic timeline metadata
+This usually improves relevance because answers are grounded in the user’s current working state.
+### DaVinci Resolve Free (Companion App)
+Resolve Free does not support the Workflow Integration plugin, so usage is via **Pygenesis Companion** (external app).
+In this mode, context is provided manually:
+- User selects the active page
+- User can optionally provide project/timeline names
+The model quality is unchanged, but contextual precision depends on the information entered by the user.
+## Practical Summary
+- **Same model weights** in Studio and Free.
+- **Studio**: automatic context -> more situational responses.
+- **Free**: manual context -> still useful responses, with lower contextual precision when input context is incomplete.
+## Recommended Use Cases
+- Resolve workflow troubleshooting ("how do I do X in Color/Fusion/Edit?").
+- Page-specific checklists ("what should I review here?").
+- Export and performance best practices.
+- Actionable next steps for practical post-production decisions.
+## Limitations
+- Not a replacement for official Blackmagic documentation.
+- Advanced workflows may still require iterative clarification.
+- In Free mode, missing manual context can reduce specificity.
+## Prompting Tips
+For best results, include:
+- Current Resolve page.
+- Clear goal ("match two shots", "export for YouTube 4K", etc.).
+- Constraints (GPU, Resolve version, footage type, deadline).
+Example:
+> "I am on the Color page. I have two shots with different exposure and need a fast matching workflow without damaging skin tones."
+## Installation & Usage
+Pygenesis ResolveExpert is distributed as a **packaged installer**, not as a manual developer setup.
+The installer handles:
+- GPU detection and inference backend selection (CUDA, Vulkan, or CPU)
+- Model download from this Hugging Face repository
+- UI installation for your Resolve edition
+After installation:
+| Edition | How you use it |
+|---------|----------------|
+| **DaVinci Resolve Studio** | Open the integrated plugin from **Workspace → Workflow Integrations → Pygenesis Resolve Tutor** |
+| **DaVinci Resolve Free** | Launch **Pygenesis Companion** (standalone app installed alongside the model) |
+Inference runs locally on your machine. No account or API key is required beyond downloading the model through the installer.
+## Intended Users
+Editors, colorists, and technical users who want a local assistant tailored to DaVinci Resolve workflows.
+## Acknowledgements
+- Built for the Pygenesis ResolveExpert project.
+- Resolve integration behavior follows Blackmagic’s Studio/Free plugin constraints.