Instructions to use ChrisColeTech/giga-lora-studio-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use ChrisColeTech/giga-lora-studio-models 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 ChrisColeTech/giga-lora-studio-models:Q8_0
# Run inference directly in the terminal:
llama cli -hf ChrisColeTech/giga-lora-studio-models:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ChrisColeTech/giga-lora-studio-models:Q8_0
# Run inference directly in the terminal:
llama cli -hf ChrisColeTech/giga-lora-studio-models:Q8_0

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 ChrisColeTech/giga-lora-studio-models:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf ChrisColeTech/giga-lora-studio-models:Q8_0

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 ChrisColeTech/giga-lora-studio-models:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ChrisColeTech/giga-lora-studio-models:Q8_0

Use Docker

docker model run hf.co/ChrisColeTech/giga-lora-studio-models:Q8_0

LM Studio
Jan
Ollama
How to use ChrisColeTech/giga-lora-studio-models with Ollama:
```
ollama run hf.co/ChrisColeTech/giga-lora-studio-models:Q8_0
```
Unsloth Desktop

How to use ChrisColeTech/giga-lora-studio-models with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ChrisColeTech/giga-lora-studio-models:Q8_0

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": "ChrisColeTech/giga-lora-studio-models:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ChrisColeTech/giga-lora-studio-models with Docker Model Runner:
```
docker model run hf.co/ChrisColeTech/giga-lora-studio-models:Q8_0
```

Lemonade

How to use ChrisColeTech/giga-lora-studio-models with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ChrisColeTech/giga-lora-studio-models:Q8_0

Run and chat with the model

lemonade run user.giga-lora-studio-models-Q8_0

List all available models

lemonade list

Hermes Agent

How to use ChrisColeTech/giga-lora-studio-models with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ChrisColeTech/giga-lora-studio-models:Q8_0

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 ChrisColeTech/giga-lora-studio-models:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ChrisColeTech/giga-lora-studio-models with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ChrisColeTech/giga-lora-studio-models:Q8_0

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 "ChrisColeTech/giga-lora-studio-models:Q8_0" \
  --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"

Giga LoRA Studio — tool models

Every model file the Giga LoRA Studio image tools download, mirrored into one repository so the app pulls from a single known source instead of five third-party accounts.

Nothing here is original work. These are redistributed copies of publicly released weights, unmodified, kept under the filenames the ComfyUI nodes expect on disk. Credit and licensing belong to the original authors, listed below.

What is here, and what uses it

Folder	Files	Used by
`BiRefNet/`	12 segmentation and matting checkpoints, plus the node's `birefnet.py`, `birefnet_lite.py`, `BiRefNet_config.py` and `config.json`	Background removal
`Lama/`	`big-lama.pt`	Watermark removal (the inpainting pass)
`grounding-dino/`	`groundingdino_swint_ogc.pth` and its config	Watermark detection (locating the mark)
`sam/`	`sam_vit_b.pth`	Watermark detection (segmenting what was located)
`upscale_models/`	`RealESRGAN_x2.pth`, `RealESRGAN_x4plus.pth`	Upscaling

Folder names match the paths the ComfyUI-RMBG node pack reads from, so a file can be dropped straight into a ComfyUI models/ tree without renaming.

Sources and licenses

Model	Upstream	License
BiRefNet (all variants except Lucida)	1038lab/BiRefNet, from ZhengPeng7/BiRefNet	Apache-2.0
Lucida	1038lab/BiRefNet	MIT
Big-LaMa	1038lab/Lama, from advimman/lama	Apache-2.0
GroundingDINO Swin-T	1038lab/GroundingDINO, from IDEA-Research/GroundingDINO	Apache-2.0
SAM ViT-B	1038lab/sam, from facebookresearch/segment-anything	Apache-2.0
Real-ESRGAN x2	ai-forever/Real-ESRGAN	BSD-3-Clause
Real-ESRGAN x4plus	xinntao/Real-ESRGAN releases	BSD-3-Clause

Each upstream project's own license terms apply to its files. If you are an author listed here and would rather this mirror did not exist, open a discussion and it will be removed.

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GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

8-bit