A 17B MoE DiT (16 double + 32 single layers, 4 routed experts) with four text encoders, on HiDreamImagePipeline (diffusers 0.39). One family covers the open Full / Dev / Fast repos (same arch); per-variant generation defaults follow the upstream inference recipes (Full 50 steps at guidance 5, the distilled Dev 28 and Fast 16 guidance-free). The repos name a Llama-3.1-8B text_encoder_4 in their model_index but do not ship its weights; the official example passes the gated meta-llama repo in by hand. The loader instead assembles the component from the open unsloth mirror (byte-identical weights, already inside the non-GGUF trust gate), injected at the three pipeline from_pretrained sites, with output_hidden_states matching the official example. Memory planning counts the assembled TE4: 34.2 GB DiT + 28.8 GB encoders, ~63 GB bf16-resident. |
||
|---|---|---|
| .. | ||
| assets | ||
| auth | ||
| core | ||
| hub | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| storage | ||
| tests | ||
| utils | ||
| __init__.py | ||
| _platform_compat.py | ||
| cloudflare_tunnel.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||
| startup_banner.py | ||