Instructions to use JohnRoger/Nomi-1.1-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with Adapters:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("fill-in-model-name")
model.load_adapter("JohnRoger/Nomi-1.1-Q8_0-GGUF", set_active=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use JohnRoger/Nomi-1.1-Q8_0-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 JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf JohnRoger/Nomi-1.1-Q8_0-GGUF: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 JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf JohnRoger/Nomi-1.1-Q8_0-GGUF: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 JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

LM Studio
Jan

vLLM

How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "JohnRoger/Nomi-1.1-Q8_0-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": "JohnRoger/Nomi-1.1-Q8_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

Ollama
How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with Ollama:
```
ollama run hf.co/JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
```
Unsloth Desktop

How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JohnRoger/Nomi-1.1-Q8_0-GGUF: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": "JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0
```

Lemonade

How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.Nomi-1.1-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use JohnRoger/Nomi-1.1-Q8_0-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 JohnRoger/Nomi-1.1-Q8_0-GGUF: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 JohnRoger/Nomi-1.1-Q8_0-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use JohnRoger/Nomi-1.1-Q8_0-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf JohnRoger/Nomi-1.1-Q8_0-GGUF: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 "JohnRoger/Nomi-1.1-Q8_0-GGUF: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"

Nomi-1.1-Q8_0-GGUF / README.md

JohnRoger

Upload README.md with huggingface_hub

c934658 verified 5 months ago

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metadata

license: apache-2.0
datasets:
  - Magpie-Align/Magpie-Pro-MT-300K-v0.1
  - Magpie-Align/Magpie-Qwen2.5-Coder-Pro-300K-v0.1
  - Magpie-Align/Magpie-Llama-3.3-Pro-500K-Filtered
language:
  - de
  - en
base_model: JallyAI/Nomi-1.1
pipeline_tag: text-generation
library_name: adapter-transformers
tags:
  - efficient
  - llama
  - llama3
  - gguf
  - ollama
  - instruction-finetuning
  - nomi
  - lazyloopstudio
  - unsloth
  - nomi1.1
  - llama-cpp
  - gguf-my-repo

JohnRoger/Nomi-1.1-Q8_0-GGUF

This model was converted to GGUF format from JallyAI/Nomi-1.1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo JohnRoger/Nomi-1.1-Q8_0-GGUF --hf-file nomi-1.1-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo JohnRoger/Nomi-1.1-Q8_0-GGUF --hf-file nomi-1.1-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo JohnRoger/Nomi-1.1-Q8_0-GGUF --hf-file nomi-1.1-q8_0.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo JohnRoger/Nomi-1.1-Q8_0-GGUF --hf-file nomi-1.1-q8_0.gguf -c 2048