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/home) for Phase 1 load-test iteration. Source bundle (slow HDD):
/storage/Models/robingg1/NAVA/.image-server/src/models/video/nava_core/ (vendored) +
build_nava.py (mmgp-driven loader, Phase 1).NAVA/
├── dit/
│ └── nava_dit_bf16.safetensors 12.59 GB 1052 tensors, 6.30B params, bf16
│ (extracted from NAVA.ckpt via
│ image-server/scripts/extract_nava_bf16.py;
│ 'backbone.' prefix STRIPPED → bare WanAVModel)
├── text_encoder/
│ ├── models_t5_umt5-xxl-enc-fp8.safetensors 6.73 GB FP8 e4m3 quanto, Wan T5Encoder
│ │ flat 'blocks.N.' layout → scaled_fp8 handler
│ │ (REUSED from Wan2.2-S2V-14B-fp8 — same frozen
│ │ Wan UMT5-XXL NAVA uses; drop-in, no remap)
│ └── google/umt5-xxl/ tokenizer (spiece.model + tokenizer.json +
│ config + special_tokens)
├── vae_video/
│ └── Wan2.2_VAE.safetensors 2.82 GB Wan2.2 TI2V 48-channel video VAE, fp32
│ (vid_in/out_dim=48; NOT the 16-ch Wan2.1 VAE.
│ Converted from .pth via scripts/pth_to_safetensors.py,
│ byte-parity verified; original .pth on /storage bundle)
├── vae_audio/
│ └── ltx-2.3-22b-dev_audio_vae.safetensors 0.36 GB Lightricks LTX-2.3 audio VAE decoder
├── config/
│ ├── config.json WanAVModel constructor config (== NAVA_6B.json):
│ │ model_type=ti2v, dim 3072, ffn 14336, heads 24,
│ │ double 10 / single 20, vid 48 / audio 128,
│ │ text_len 512, qk_norm, temporal_rope_scale 0.24
│ ├── nava.yaml pipeline/inference config (guidance scales,
│ │ shift=5, unipc, 4-pass CFG flags)
│ └── example_prompts.jsonl 5 sample prompts (prompt / spk_wavs / image_path)patch_embedding.weight, single_blocks.0...) — the
backbone. prefix from the training checkpoint was stripped, so this loads directly into a
bare WanAVModel. Strict-load key-match against WanAVModel.state_dict() is the Phase 1 gate./storage/Models/robingg1/NAVA/Wan2.2-TI2V-5B/models_t5_umt5-xxl-enc-bf16.pth (11.36 GB).scripts/quantize_nava_fp8.py and dropped into
dit/nava_dit_fp8.safetensors alongside the bf16.model_id: Qwen3-1.7B in nava.yaml is prompt-rewriting only, not the model.project_nava_kernel_fit.md.