Instructions to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF 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 sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

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 sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

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 sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

Use Docker

docker model run hf.co/sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sphaela/Ornith-1.0-9B-AutoRound-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sphaela/Ornith-1.0-9B-AutoRound-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

Ollama
How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with Ollama:
```
ollama run hf.co/sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
```
Unsloth Desktop

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF: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": "sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with Docker Model Runner:
```
docker model run hf.co/sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M
```

Lemonade

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Ornith-1.0-9B-AutoRound-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF: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 sphaela/Ornith-1.0-9B-AutoRound-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use sphaela/Ornith-1.0-9B-AutoRound-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sphaela/Ornith-1.0-9B-AutoRound-GGUF: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 "sphaela/Ornith-1.0-9B-AutoRound-GGUF: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"

sphaela commited on Jun 30

Commit

5190bca

verified ·

1 Parent(s): b8727dd

Upload comparison.csv with huggingface_hub

Browse files

Files changed (1) hide show

comparison.csv +0 -3

comparison.csv CHANGED Viewed

@@ -2,11 +2,8 @@ scheme,size_gb,bpw,ppl,dppl_pct,kld_mean,kld_q99,top1_agree_pct
 Q2_K_S,3.697238496,3.303390424817804,9.893337,21.737732477248326,0.295998,2.746646,76.829
 Q3_K_S,4.259406304,3.8056733465436126,8.527342,4.929133530779726,0.121556,1.086482,84.995
 Q3_K_M,4.516569568,4.035442311902912,8.569239,5.44467705038278,0.121405,1.068216,84.866
-Q2_K_MIXED,4.690518496,4.190861342561658,71.871501,784.38042305405,2.279515,8.398958,38.414
 Q3_K_L,4.925514208,4.400824152841248,8.600858,5.8337495507128745,0.120064,1.056818,84.898
 Q4_K_S,5.35162928,4.781547346716418,8.047454,-0.9758990141585313,0.042472,0.359782,91.014
 Q4_K_M,5.629108704,5.029468294558231,8.075174,-0.6348037958040598,0.040609,0.348605,91.209
-Q5_K_S,6.305309152,5.6336365373149215,8.362478,2.900478333132134,0.067028,0.531329,88.632
-Q5_K_M,6.467969504,5.778969506739433,8.312082,2.280354428940524,0.061514,0.498653,89.222
 Q6_K,7.359259104,6.575314544681959,8.150005,0.28599332846300257,0.00402,0.025164,96.639
 Q8_0,9.52750128,8.51258487512821,8.136132,0.11528575399577318,0.002044,0.012462,97.51

 Q2_K_S,3.697238496,3.303390424817804,9.893337,21.737732477248326,0.295998,2.746646,76.829
 Q3_K_S,4.259406304,3.8056733465436126,8.527342,4.929133530779726,0.121556,1.086482,84.995
 Q3_K_M,4.516569568,4.035442311902912,8.569239,5.44467705038278,0.121405,1.068216,84.866
 Q3_K_L,4.925514208,4.400824152841248,8.600858,5.8337495507128745,0.120064,1.056818,84.898
 Q4_K_S,5.35162928,4.781547346716418,8.047454,-0.9758990141585313,0.042472,0.359782,91.014
 Q4_K_M,5.629108704,5.029468294558231,8.075174,-0.6348037958040598,0.040609,0.348605,91.209
 Q6_K,7.359259104,6.575314544681959,8.150005,0.28599332846300257,0.00402,0.025164,96.639
 Q8_0,9.52750128,8.51258487512821,8.136132,0.11528575399577318,0.002044,0.012462,97.51