Instructions to use elichen-skymizer/GAP-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 elichen-skymizer/GAP-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 elichen-skymizer/GAP-models:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf elichen-skymizer/GAP-models:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf elichen-skymizer/GAP-models:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf elichen-skymizer/GAP-models:UD-Q4_K_XL

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 elichen-skymizer/GAP-models:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama cli -hf elichen-skymizer/GAP-models:UD-Q4_K_XL

Use Docker

docker model run hf.co/elichen-skymizer/GAP-models:UD-Q4_K_XL

Llama new
LM Studio
Jan
Ollama
How to use elichen-skymizer/GAP-models with Ollama:
```
ollama run hf.co/elichen-skymizer/GAP-models:UD-Q4_K_XL
```
Unsloth Desktop

How to use elichen-skymizer/GAP-models with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf elichen-skymizer/GAP-models:UD-Q4_K_XL

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": "elichen-skymizer/GAP-models:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use elichen-skymizer/GAP-models with Docker Model Runner:
```
docker model run hf.co/elichen-skymizer/GAP-models:UD-Q4_K_XL
```

Lemonade

How to use elichen-skymizer/GAP-models with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull elichen-skymizer/GAP-models:UD-Q4_K_XL

Run and chat with the model

lemonade run user.GAP-models-UD-Q4_K_XL

List all available models

lemonade list

Hermes Agent

How to use elichen-skymizer/GAP-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 elichen-skymizer/GAP-models:UD-Q4_K_XL

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 elichen-skymizer/GAP-models:UD-Q4_K_XL

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use elichen-skymizer/GAP-models with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf elichen-skymizer/GAP-models:UD-Q4_K_XL

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 "elichen-skymizer/GAP-models:UD-Q4_K_XL" \
  --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"

GAP-models / bpw /report-validation.json

elichen-skymizer

Upload folder using huggingface_hub

b2a9359 verified about 2 months ago

Raw History Blame Contribute Delete

426 Bytes

{
  "status": "passed",
  "rows": 70,
  "families": 8,
  "visible_gguf_files_accounted_for": 89,
  "main_files": 74,
  "excluded_files": 15,
  "markdown_links_verified": 82,
  "bash_syntax": "passed",
  "hf_estimates_match_native_all_parameters": true,
  "validation_source": "refresh-validation.json",
  "review_scope": "REVIEW.md documents the earlier scanner review; current data revalidated in refresh-validation.json."
}

	{
	"status": "passed",
	"rows": 70,
	"families": 8,
	"visible_gguf_files_accounted_for": 89,
	"main_files": 74,
	"excluded_files": 15,
	"markdown_links_verified": 82,
	"bash_syntax": "passed",
	"hf_estimates_match_native_all_parameters": true,
	"validation_source": "refresh-validation.json",
	"review_scope": "REVIEW.md documents the earlier scanner review; current data revalidated in refresh-validation.json."
	}