```python
>>> import json
>>> import safetensors.torch
>>> from huggingface_hub import read_dduf_file

# Read DDUF metadata
>>> dduf_entries = read_dduf_file("FLUX.1-dev.dduf")

# Returns a mapping filename <> DDUFEntry
>>> dduf_entries["model_index.json"]
DDUFEntry(filename='model_index.json', offset=66, length=587)

# Load model index as JSON
>>> json.loads(dduf_entries["model_index.json"].read_text())
{'_class_name': 'FluxPipeline', '_diffusers_version': '0.32.0.dev0', '_name_or_path': 'black-forest-labs/FLUX.1-dev', 'scheduler': ['diffusers', 'FlowMatchEulerDiscreteScheduler'], 'text_encoder': ['transformers', 'CLIPTextModel'], 'text_encoder_2': ['transformers', 'T5EncoderModel'], 'tokenizer': ['transformers', 'CLIPTokenizer'], 'tokenizer_2': ['transformers', 'T5TokenizerFast'], 'transformer': ['diffusers', 'FluxTransformer2DModel'], 'vae': ['diffusers', 'AutoencoderKL']}

# Load VAE weights using safetensors
>>> with dduf_entries["vae/diffusion_pytorch_model.safetensors"].as_mmap() as mm:
...     state_dict = safetensors.torch.load(mm)
```