jide/qwen-test

Qwen Image Layered - Docker Deployment for HF Inference Endpoints

This directory contains a custom Docker-based deployment for QwenImageLayeredPipeline.

Files

• Dockerfile: Custom container with all bleeding-edge dependencies.
• app.py: FastAPI server (HF-compatible API format).
• handler.py: Model loading and inference logic.
• requirements.txt: Python dependencies (all from git main).

Deployment Steps

1. Build and Push Docker Image

# Login to Docker Hub (or another registry)
docker login

# Build the image
docker build -t yourusername/qwen-layered:latest .

# Push to registry
docker push yourusername/qwen-layered:latest

2. Create HF Inference Endpoint

1. Go to HF Inference Endpoints
2. Click New Endpoint
3. Select Custom Container
4. Enter your Docker image URL: docker.io/yourusername/qwen-layered:latest
5. Select GPU (A10G or better, 24GB+ VRAM)
6. Deploy

3. Usage

curl https://your-endpoint.endpoints.huggingface.cloud \
  -X POST \
  -d '{"inputs": {"prompt": "A cute cat"}}' \
  -H "Authorization: Bearer hf_..." \
  -H "Content-Type: application/json"

Local Testing

docker build -t qwen-test .
docker run --gpus all -p 8080:8080 qwen-test
# Then: curl http://localhost:8080/health