Instructions to use aelgendy/QModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aelgendy/QModel with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="aelgendy/QModel",
	filename="models/Qwen3-32B-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use aelgendy/QModel with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aelgendy/QModel:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf aelgendy/QModel:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf aelgendy/QModel:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf aelgendy/QModel: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 aelgendy/QModel:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf aelgendy/QModel: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 aelgendy/QModel:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf aelgendy/QModel:Q4_K_M

Use Docker

docker model run hf.co/aelgendy/QModel:Q4_K_M

LM Studio
Jan
Ollama
How to use aelgendy/QModel with Ollama:
```
ollama run hf.co/aelgendy/QModel:Q4_K_M
```

Unsloth Studio new

How to use aelgendy/QModel with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for aelgendy/QModel to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for aelgendy/QModel to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for aelgendy/QModel to start chatting

Pi new

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-server -hf aelgendy/QModel:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/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:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

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-server -hf aelgendy/QModel: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 aelgendy/QModel:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use aelgendy/QModel with Docker Model Runner:
```
docker model run hf.co/aelgendy/QModel:Q4_K_M
```

Lemonade

How to use aelgendy/QModel with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull aelgendy/QModel:Q4_K_M

Run and chat with the model

lemonade run user.QModel-Q4_K_M

List all available models

lemonade list

aelgendy commited on Mar 25

Commit

7ecdf4a

1 Parent(s): 52c235e

Upload folder using huggingface_hub

Browse files

Files changed (6) hide show

.env.example +1 -1
DOCKER.md +3 -3
Dockerfile +2 -2
OPEN_WEBUI.md +3 -3
README.md +2 -2
SETUP.md +1 -1

.env.example CHANGED Viewed

@@ -1,4 +1,4 @@
-# QModel v4 Configuration Template
 # ==================================
 # Copy this to .env and update values for your environment

+# QModel 6 Configuration Template
 # ==================================
 # Copy this to .env and update values for your environment

DOCKER.md CHANGED Viewed

@@ -271,15 +271,15 @@ docker build -t qmodel:custom .
 ```bash
 # Tag for registry
-docker tag qmodel myregistry/qmodel:v4.1
 # Push
-docker push myregistry/qmodel:v4.1
 # Run from registry
 docker run -p 8000:8000 \
   --env-file .env \
-  myregistry/qmodel:v4.1
 ```
 ---

 ```bash
 # Tag for registry
+docker tag qmodel myregistry/qmodel:v6.1
 # Push
+docker push myregistry/qmodel:v6.1
 # Run from registry
 docker run -p 8000:8000 \
   --env-file .env \
+  myregistry/qmodel:v6.1
 ```
 ---

Dockerfile CHANGED Viewed

@@ -1,4 +1,4 @@
-# QModel v4 - Islamic RAG API
 # =============================
 # Dockerfile for QModel API
 # Supports both Ollama and HuggingFace backends via .env configuration
@@ -10,7 +10,7 @@ FROM python:3.11-slim
 # Metadata
 LABEL maintainer="QModel Team"
-LABEL description="QModel v4 - Quran & Hadith RAG API"
 LABEL version="4.1"
 # Environment variables

+# QModel 6 - Islamic RAG API
 # =============================
 # Dockerfile for QModel API
 # Supports both Ollama and HuggingFace backends via .env configuration
 # Metadata
 LABEL maintainer="QModel Team"
+LABEL description="QModel v6 - Quran & Hadith RAG API"
 LABEL version="4.1"
 # Environment variables

OPEN_WEBUI.md CHANGED Viewed

@@ -1,6 +1,6 @@
-# Using QModel v4 with Open-WebUI
-QModel v4 is fully compatible with **Open-WebUI** thanks to its OpenAI-compatible API endpoints. This guide shows you how to integrate them.
 ## Prerequisites
@@ -367,7 +367,7 @@ curl -X POST http://localhost:8000/v1/chat/completions \
 1. **Restrict CORS**: Set `ALLOWED_ORIGINS=your-domain.com` in `.env`
 2. **Use HTTPS**: Proxy through nginx with TLS
-3. **Rate limit**: Add rate limiting middleware (not in v4, but recommended)
 4. **Authentication**: Consider adding API key validation layer
 5. **Network**: Don't expose QModel directly to the internet without auth

+# Using QModel v6 with Open-WebUI
+QModel v6 is fully compatible with **Open-WebUI** thanks to its OpenAI-compatible API endpoints. This guide shows you how to integrate them.
 ## Prerequisites
 1. **Restrict CORS**: Set `ALLOWED_ORIGINS=your-domain.com` in `.env`
 2. **Use HTTPS**: Proxy through nginx with TLS
+3. **Rate limit**: Add rate limiting middleware (not in v6, but recommended)
 4. **Authentication**: Consider adding API key validation layer
 5. **Network**: Don't expose QModel directly to the internet without auth

README.md CHANGED Viewed

@@ -19,7 +19,7 @@ language:
   - en
 ---
-# QModel v4 — Islamic RAG System
 **Specialized Qur'an & Hadith Knowledge System with Dual LLM Support**
 > A production-ready Retrieval-Augmented Generation system specialized exclusively in authenticated Islamic knowledge. No hallucinations, no outside knowledge—only content from verified sources.
@@ -279,7 +279,7 @@ See [SETUP.md](SETUP.md) and [DOCKER.md](DOCKER.md) for more detailed troublesho
 ---
-## What's New in v4
 ✨ **Dual LLM Backend** — Ollama (dev) + HuggingFace (prod)
 ✨ **Grade Filtering** — Return only Sahih/Hasan authenticated Hadiths

   - en
 ---
+# QModel 6 — Islamic RAG System
 **Specialized Qur'an & Hadith Knowledge System with Dual LLM Support**
 > A production-ready Retrieval-Augmented Generation system specialized exclusively in authenticated Islamic knowledge. No hallucinations, no outside knowledge—only content from verified sources.
 ---
+## What's New in v6
 ✨ **Dual LLM Backend** — Ollama (dev) + HuggingFace (prod)
 ✨ **Grade Filtering** — Return only Sahih/Hasan authenticated Hadiths

SETUP.md CHANGED Viewed

@@ -1,4 +1,4 @@
-# QModel v4 Setup & Deployment Guide
 ## Quick Start


1	+ # QModel v6 Setup & Deployment Guide
2
3	## Quick Start
4