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1pip install torch pillow transformers
2git lfs install
3git clone https://huggingface.co/Enzo8930302/ByteDream
4cd ByteDream1from bytedream import ByteDreamGenerator
2
3# Load model
4generator = ByteDreamGenerator(hf_repo_id="Enzo8930302/ByteDream")
5
6# Generate image
7image = generator.generate(
8 prompt="A beautiful sunset over mountains, digital art",
9 num_inference_steps=50,
10 guidance_scale=7.5,
11)
12image.save("output.png")1from bytedream import ByteDreamHFClient
2
3client = ByteDreamHFClient(
4 repo_id="Enzo8930302/ByteDream",
5 use_api=True,
6)
7
8image = client.generate(
9 prompt="Futuristic city at night, cyberpunk",
10)
11image.save("output.png")1# Create dataset
2python create_test_dataset.py
3
4# Train model
5python train.py --config config.yaml --train_data datasetpython app.pypython deploy_to_spaces.py --repo_id YourUsername/ByteDream-SpaceByteDream/
├── bytedream/ # Core package
│ ├── __init__.py
│ ├── generator.py # Main generator
│ ├── model.py # Model architecture
│ ├── pipeline.py # Pipeline
│ ├── scheduler.py # Scheduler
│ ├── hf_api.py # HF API client
│ └── utils.py
├── train.py # Training script
├── infer.py # Inference
├── app.py # Web UI
├── config.yaml # Config
└── requirements.txt # Dependenciesrequirements.txt for full list.1@software{bytedream2024,
2 title={Byte Dream: CPU-Optimized Text-to-Image Generation},
3 year={2024}
4}