Instructions to use aelgendy/QModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use aelgendy/QModel 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 aelgendy/QModel:Q8_0 # Run inference directly in the terminal: llama cli -hf aelgendy/QModel:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf aelgendy/QModel:Q8_0 # Run inference directly in the terminal: llama cli -hf aelgendy/QModel:Q8_0
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 aelgendy/QModel:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf aelgendy/QModel:Q8_0
Use Docker
docker model run hf.co/aelgendy/QModel:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use aelgendy/QModel with Ollama:
ollama run hf.co/aelgendy/QModel:Q8_0
- Unsloth Desktop
- Pi
How to use aelgendy/QModel with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aelgendy/QModel: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": "aelgendy/QModel:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use aelgendy/QModel with Docker Model Runner:
docker model run hf.co/aelgendy/QModel:Q8_0
- Lemonade
How to use aelgendy/QModel with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aelgendy/QModel:Q8_0
Run and chat with the model
lemonade run user.QModel-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use aelgendy/QModel with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aelgendy/QModel: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 aelgendy/QModel:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use aelgendy/QModel with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf aelgendy/QModel: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 "aelgendy/QModel: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"
File size: 2,051 Bytes
506e3fd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | #!/usr/bin/env python3
"""
Safely sync or upload files/folders to Hugging Face Hub (aelgendy/QModel).
Automatically excludes sensitive or local folders (.claude, .vscode, .env, .venv, scratch, data).
"""
import argparse
import sys
import os
# Auto-fallback to Homebrew hf Python if huggingface_hub is not in current environment
try:
from huggingface_hub import HfApi
except ImportError:
brew_python = "/opt/homebrew/Cellar/hf/2.2.0/libexec/bin/python"
if os.path.exists(brew_python) and sys.executable != brew_python:
os.execv(brew_python, [brew_python] + sys.argv)
raise
DEFAULT_IGNORE = [
".claude/**",
".vscode/**",
".env*",
".venv/**",
"scratch/**",
"data/**",
"__pycache__/**",
"*.pyc",
".DS_Store",
]
def main():
parser = argparse.ArgumentParser(description="Upload to Hugging Face with safety exclusions.")
parser.add_argument("--repo-id", default="aelgendy/QModel", help="HF Repo ID (default: aelgendy/QModel)")
parser.add_argument("--repo-type", default="model", choices=["model", "dataset", "space"], help="Repository type")
parser.add_argument("--folder", default=".", help="Local folder to upload (default: current directory)")
parser.add_argument("--message", default="Sync repository to Hugging Face", help="Commit message")
parser.add_argument("--include-models", action="store_true", help="Include models/ directory in upload")
args = parser.parse_args()
ignore = list(DEFAULT_IGNORE)
if not args.include_models:
ignore.append("models/**")
ignore.append("*.gguf")
print(f"Uploading '{args.folder}' to '{args.repo_id}' (repo_type={args.repo_type})...")
print(f"Ignored patterns: {ignore}")
api = HfApi()
commit = api.upload_folder(
repo_id=args.repo_id,
folder_path=args.folder,
repo_type=args.repo_type,
commit_message=args.message,
ignore_patterns=ignore,
)
print(f"Successfully uploaded! Commit URL: {commit}")
if __name__ == "__main__":
main()
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