Complete runtime checkpoints and remove native video VAE dependency

Add upstream Qwen conditioning in original and runtime DCP formats, official H3 TAE, audio codec, tokenizer/processor and complete runtime asset manifest. Causal decoder now constructs the student directly without a native video VAE checkpoint. Remove the external-dependency chapter; preserve MiniMax-H3-only acknowledgements and all applicable upstream licenses. No trained renderer/decoder weight changes.

.gitattributes

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+qwen_dcp/.metadata filter=lfs diff=lfs merge=lfs -text
+qwen_dcp/__0_0.distcp filter=lfs diff=lfs merge=lfs -text
+qwen_dcp/__1_0.distcp filter=lfs diff=lfs merge=lfs -text
+qwen_dcp/__2_0.distcp filter=lfs diff=lfs merge=lfs -text
+qwen_dcp/__3_0.distcp filter=lfs diff=lfs merge=lfs -text
+reference_image/ref.png filter=lfs diff=lfs merge=lfs -text

LICENSE-Qwen.txt

@@ -0,0 +1,201 @@
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LICENSE-TAE.txt

@@ -0,0 +1,21 @@
+# SPDX-License-Identifier: MIT
+#
+# Copyright (c) 2025 Ollin Boer Bohan
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.

NOTICE

@@ -1,4 +1,10 @@
 MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
 
-Modified weights: StreamRender-H3 1008b step224 merged EMA streaming renderer; Fast Causal H3 VAE ViT24 decoder, distilled step6000, release 20261005-v1.
-Both are derivatives of MiniMax-H3. Upstream license terms remain applicable; see LICENSE.
+The StreamRender-H3 backbone is a modified, fine-tuned MiniMax H3 derivative:
+1008b timeline-critic native DMD, step224, two denoising evaluations, merged EMA.
+The causal ViT24 decoder is a modified/distilled H3 decoder, step6000, release 20261005-v1.
+Upstream model license terms remain applicable. See LICENSE.
+Qwen3-VL components retain their upstream Apache-2.0 license; see LICENSE-Qwen.txt.
+TAE implementation attribution: Copyright (c) 2025 Ollin Boer Bohan; see LICENSE-TAE.txt.
+
+Runtime code: https://github.com/NVlabs/Sana/tree/sol-engine/models/streamrender_h3

README.md

@@ -20,23 +20,30 @@ StreamRender-H3 splits an interactive world into a **Code Game Engine** and a **
 - Diffusion render of 217.96 ms per streaming step on 8 GB200 GPUs, a 3.67× speedup over the PyTorch baseline.
 - Fast Causal H3 VAE decodes 2 latent frames at 720p in 24 ms on one GB200, built by a self-improving agent loop.
 
-## Released weights
+## Released runtime assets
 
-This repository contains **two trained model components**:
+This repository contains the complete model assets for the streaming runtime.
 
-| Directory | Model | Checkpoint |
+| Directory | Component | Weight provenance |
 | --- | --- | --- |
-| `backbone/` | Streaming H3 renderer, full 50-layer EMA backbone with LoRA merged | 1008b / step224 |
-| `causal_decoder/` | Fast Causal H3 VAE, a pruned and distilled 24-layer causal decoder | step6000 / 20261005-v1 |
-
-The renderer uses two denoising evaluations with the S=2/W=2/C=2 streaming
-policy. The decoder processes two available latent frames per call, using
-cached past context without future latent frames. These are the trained
-renderer and decoder checkpoints, not a bundle of unchanged upstream models.
+| `backbone/` | Full 50-layer streaming H3 renderer, 1008b step224 EMA, LoRA merged | Trained renderer |
+| `causal_decoder/` | Fast Causal H3 VAE, distilled ViT24 decoder step6000 | Trained decoder |
+| `qwen_model/`, `qwen_dcp/` | H3-compatible Qwen conditioning model in safetensors and DCP formats | Unchanged upstream model; DCP is a storage conversion |
+| `tae/` | Official H3 TAE weights for streaming reference encoding | Unchanged upstream weights |
+| `audio_vae/` | H3 audio codec required by the model contract | Unchanged upstream weights |
+| `tokenizer/`, `qwen_processor/` | Conditioning tokenizer and processor | Upstream runtime assets |
+| `configs/`, `assets.json` | Runtime configuration, environment versions, relative asset manifest | Deployment configuration |
+| `reference_image/` | Default B10_e-track-3_bluehour reference picture | Example initialization asset |
+
+There are five distinct model components. Qwen's two storage formats are the
+same model. The causal decoder is constructed directly from its architecture
+configuration and student checkpoint; no native H3 video VAE checkpoint is
+needed. Streaming reference encoding uses TAE, and video decoding uses the
+trained causal decoder.
 
 ## Download and use
 
-Runtime code and deployment instructions:
+Code and full deployment instructions:
 [NVlabs/Sana — StreamRender-H3](https://github.com/NVlabs/Sana/tree/sol-engine/models/streamrender_h3).
 
 ```python
@@ -45,22 +52,29 @@ snapshot_download("Efficient-Large-Model/StreamRender-H3",
                   local_dir="./StreamRender-H3")
 ```
 
-The download is approximately 72.75 GB. The renderer is stored as nine
-safetensors shards, preserving all original tensor values. The current
-runtime expects one merged backbone file. Reconstruct it with:
+The complete assets are approximately 206.87 GB. Reconstruct the exact
+merged backbone from its nine safetensors shards (another 66.28 GB of disk):
 
 ```bash
 python StreamRender-H3/download_assets.py
+cd Sana/models/streamrender_h3
+python scripts/preflight.py --assets /absolute/path/to/StreamRender-H3/assets.json
+GPUS=8 PYTHON_BIN=python bash scripts/launch_local.sh \
+  --config /absolute/path/to/StreamRender-H3/configs/runtime.json \
+  --assets /absolute/path/to/StreamRender-H3/assets.json
 ```
 
-Reconstruction needs another 66.28 GB of disk and verifies the original
-SHA-256. Point the runtime manifest's `backbone` entry to
-`backbone/1008b_step224_backbone_ema_merged.safetensors` and its
-`causal_decoder` entry to `causal_decoder/causal_vit24_step6000.safetensors`.
-Provide the remaining runtime dependencies separately as described in the
-runtime README and `configs/assets.example.json`; this release contains
-only the two trained model components. `SHA256SUMS` and `inventory.json`
-provide integrity information for the released files.
+Use the documented Python/CUDA environment and install frontend dependencies
+first. The bundle includes compatible Qwen DCP weights, so no separate DCP
+conversion or personal model repository is required. The default prompt and
+reference image are B10_e-track-3_bluehour. Alternative semantic-video examples
+and their media download instructions are in the runtime's `examples/` folder.
+
+The runtime uses eight GPUs in one NVLink domain, two full denoising evaluations,
+CFG=1 and S=2/W=2/C=2. Qwen conditions on the prompt and first picture once per
+session. `SHA256SUMS` records file integrity. Each component retains its
+applicable upstream license; see `LICENSE`, `LICENSE-Qwen.txt`,
+`LICENSE-TAE.txt`, and `NOTICE`.
 
 ## License
 

SHA256SUMS

@@ -1,6 +1,10 @@
 59b99642b95ea21630e311198ddbfffbfe05aadba0c2f5d884cbdf4efcc90f44  LICENSE
-48edcb6a7daab4034f94b829a2a135c0ac9c477eb6db756161af5f19a4ac118c  NOTICE
-432a2b2f6886a76f61c16afcad59a4517df2c9cac9f4afb7a7dc6e1b6cd4b6ea  README.md
+c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4  LICENSE-Qwen.txt
+632b629922abb525fce6dd828ccb87f535f4f5fe69830bd43f2e87f2110a8a00  LICENSE-TAE.txt
+30f8403c924f43355102d88428161f88a287882ab86a52ba4d70e1617f55ca2a  NOTICE
+c1b16e2eecb42feac6b3949aa23064cc99f61555a3734f3da4f952013e5b5ce2  README.md
+0c6bd3cd03575dbadf4d26421df9b4dab8a86afffa741505b581d2c21d79b293  assets.json
+37dddc2f3e6d5d5139d823d5ea283bbf304dadcb885b1ccda818aa13dade5ea2  audio_vae/model.safetensors
 46c17356261c81b43309da11824cc62072df0f4fa9c102a0b5ecdeb42085d8f2  backbone/model-00001-of-00009.safetensors
 7d943cc7fbb9d3d3d16f5bd1c09d56f17c720f5b90ff7f261f576d164ce8e5a2  backbone/model-00002-of-00009.safetensors
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-503af8e015ef6b74a70bdbecedb4b43f735b4c4c219ee8b1753d45ef89ececc3  download_assets.py
-2490bb91fa7e780045f70d54a1f467054831654826e6878770d25a79018ff779  inventory.json
+a7dc114b2e8b0d3aa9cb1b2d8c3908796db4846bca2e76183901d82f96461ada  configs/environment-tested.json
+983db945c3c2212d3f63ef8cb3bd3380d0416a6ad3192b8f41b9c90debc8437b  configs/runtime.json
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+ce63c0c62e6d297b81ea705fb318679cca530dcaed17b86ed2c5098d25e7d818  qwen_dcp/.metadata
+e7968e3ab9b1d84353eae9d4ba2ee104798e1e27448179bcfd424c9f0529e72b  qwen_dcp/__0_0.distcp
+0a60fcbcf97452397dd81e0108d32486c337f8a0b09efcde94061581c57b1c42  qwen_dcp/__1_0.distcp
+afecba699073977706642fcbcd0eed3b0fc49b4e97902cc6e9585b071ea3f1d3  qwen_dcp/__2_0.distcp
+dd2edd5d0b0a7cb0a724180dfc9f9879dd2c2ef1146e7945b04a9cccf1f1ecec  qwen_dcp/__3_0.distcp
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+a07e942ac874baa13758de8d1fbdb186683cc03416b5589e1b6671c6b3057c68  qwen_processor/tokenizer_config.json
+7768af27c1fafa9cc9011c1dc20067e03f8915e03b63504550e11d5066986d13  qwen_processor/video_preprocessor_config.json
+ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910  qwen_processor/vocab.json
+609f7fcf9311c97b20af9fa842b26bd223f5f1836040ae50bb2191ea3eb40b57  reference_image/ref.png
+af92965c2d7986a89a757e7cccd26f9eeeff0c3f0d5495eb168aeb2d6d9be9ba  tae/taeh3_official.pth
+599bab54075088774b1733fde865d5bd747cbcc7a547c5bc12610e874e26f5e3  tokenizer/merges.txt
+a5d85b6dcc535e6b93115a9ef287e6132fdbf30270da6218194ba742261173c7  tokenizer/tokenizer.json
+a07e942ac874baa13758de8d1fbdb186683cc03416b5589e1b6671c6b3057c68  tokenizer/tokenizer_config.json
+ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910  tokenizer/vocab.json

assets.json

@@ -0,0 +1,16 @@
+{
+  "schema": 1,
+  "assets": {
+    "tokenizer": "tokenizer",
+    "qwen_processor": "qwen_processor",
+    "qwen_model": "qwen_model",
+    "qwen_dcp": "qwen_dcp",
+    "tae": "tae/taeh3_official.pth",
+    "causal_decoder": "causal_decoder/causal_vit24_step6000.safetensors",
+    "audio_vae": "audio_vae/model.safetensors",
+    "reference_image": "reference_image/ref.png",
+    "prompt": "subject_definitions:\n<Picture 1> is the first-frame anchor of the target video: a photorealistic AAA re-render of the opening frame of <Video 1>, which fixes the starting composition and the look of every subject, including paint, materials, lighting, and color grading.\n<Video 1> is a semantic segmentation video of the same drive and the structural template for the target video: every pixel is painted one flat label color according to its object class, and it supplies the road layout, every car's silhouette, position, and movement, and the chase-camera trajectory frame by frame. Purple is the dark asphalt race track reflecting trackside lights, magenta is the red-and-white kerb and muted green painted run-off strip at the left track edge, green is shadowed grass meadows and verges lit by floodlights, olive is dark trees, woodland, and forested hillsides, orange is the illuminated galvanized armco guard rails, dark grey is the steel posts and scaffold legs of the billboards, cyan is the glowing sponsor billboards and hoardings, steel blue is the deep cobalt twilight sky with an orange-pink horizon, red is the player's car, and blue is the rival car. These colors are class labels only and are not the colors or textures of the target video.\n<Subject 1> is the player's car, a modern rally-derived four-door touring race sedan whose silhouette, position, and motion come from the red region of <Video 1> and whose appearance comes from <Picture 1>: glossy deep racing-red paint catching crisp white floodlight highlights, a scuffed white lower rear bumper panel with a black \"KESTREL\" wordmark and small \"VOLTEX\" decals at its corners, a yellow trunk plate reading \"AUREL MOTORSPORT\", a full-width dark rear wing with red endplates on the trunk lid, a white roll-cage X-brace visible through the rear window, a thin roof antenna, black door mirrors, brightly illuminated red LED tail-light clusters and a central red rear light, a carbon diffuser with strakes and a single polished exhaust tip on the right, and road grime and chipped paint along the lower body.\n<Subject 2> is the field of rival cars, here a single GT race car with a tall rear wing, a dark red body under cool floodlight highlights and deep shadow, and glowing red tail lights, whose silhouette, position, and motion come from the blue regions of <Video 1> and whose appearance comes from <Picture 1>.\n<Subject 3> is the track and its surroundings, whose layout comes from <Video 1> and whose look comes from <Picture 1>: dark-grey asphalt with coarse aggregate, tar seams, rubber marks, crisp white edge lines, and elongated light reflections, galvanized armco guard rails on posts, shadowed grass meadows with wildflowers, rolling hills with dark mixed woodland and blue atmospheric haze, and illuminated sponsor billboards, including the red-and-white kerb, muted green painted run-off strip, grey asphalt run-off, lone oak, and black-and-grey checkered \"VELTRA RACING\" billboards beneath tall white trackside floodlights.\n\nsummary:\n[keyframe completion + reference generation] The target video is a photorealistic Forza Horizon-style chase-camera drive on an asphalt circuit winding through dark green hills and woodland at blue hour just after sunset, with a deep cobalt sky, the last warm horizon glow, and bright trackside floodlights. It begins exactly from <Picture 1>, which fixes the look of <Subject 1>, <Subject 2>, and <Subject 3>, while <Video 1> supplies the road layout, every car's silhouette and movement, and the camera path as <Subject 1> runs the general course of this drive: over gentle crests and through dips, along straights lined with armco rails and sponsor hoardings, and through long sweeping bends, while <Subject 2> runs far ahead.\n\nretention_analysis:\n<Picture 1> ([Shot 1] first frame): fully_preserved - the opening composition, car placement, floodlight direction, twilight horizon, and grading are kept exactly.\n<Video 1> (structural template for layout, motion, and camera): fully_preserved - road course, car silhouettes, positions, movement, and camera trajectory follow it frame by frame, while its flat label colors are not rendered.\n<Subject 1> (appears in [Shot 1]): fully_preserved - red race sedan with its wing, livery, plates, and exhaust stays identical and holds the lower center of the frame.\n<Subject 2> (appears in [Shot 1]): fully_preserved - the dark red GT car keeps its floodlit appearance and red tail lights whenever it is visible and moves as the blue regions of <Video 1> dictate, including as a tiny shape in the distance.\n<Subject 3> (appears in [Shot 1]): fully_preserved - asphalt, kerbs, run-off, armco rails, sponsor billboards, meadows, lone trees, woodland, and shadowed hills keep the look of <Picture 1>.\n\ndetailed_description:\nThe target video is a photorealistic AAA racing-game render in the style of Forza Horizon at maximum settings: blue hour just after sunset turning into night, a deep cobalt sky crossed by dark cloud bands and a narrow orange-pink glow behind the distant wooded ridge, tall trackside floodlights casting crisp white pools downward from both sides of the circuit, bright specular highlights across the car's roof, wing, and mirrors, localized shadows beneath cars and trees, cool blue shade between illuminated areas, and warm smaller lamps edging the rails and lighting sponsor boards. The cars' headlights and red tail lights are on; glossy paint, metallic barriers, and textured asphalt catch white, amber, and red reflections. Deep contrast, high dynamic range, ray-traced reflections, and cinematic grading balance cobalt shadows with neutral white highlights and the last warm sunset colors. Everything is crisp and densely detailed, with slight speed blur on the road surface only; there is no HUD, speedometer, minimap, lap or position counter, timer, watermark, caption, or overlay text, and no flat-colored or segmentation-map look.\n[Shot 1] The camera is one continuous chase-camera tracking shot behind <Subject 1> that follows the exact path and sway of <Video 1>, with no zoom, no pan, and no reframing; the shot never cuts. The shot begins from <Picture 1>. <Subject 1> sits in the lower center of the frame, seen from directly behind: glossy racing-red body, scuffed white lower bumper panel with the black \"KESTREL\" wordmark, yellow \"AUREL MOTORSPORT\" plate, full-width dark rear wing with red endplates, white roll-cage X-brace behind the rear window, and one polished exhaust tip on the right, its bright rear lights casting red reflections immediately behind it. Far ahead, just right of center at the crest, <Subject 2>, the dark red GT car with a tall rear wing, glows with red tail lights. On the left run a red-and-white kerb, a muted green painted run-off strip, and a wide grey asphalt run-off bounded by an armco rail, with a lamp-lit meadow rising to a lone oak silhouetted against the orange twilight horizon; on the right a grass verge, an armco rail, and three large black-and-grey checkered billboards reading \"VELTRA RACING\" in bold yellow italic capitals, illuminated by warm overhead fixtures. Throughout the drive, every car's position and movement, the course of the road, and the camera's path and sway follow <Video 1> exactly. The road rises over gentle crests, dips through shallow hollows and small kinks, and sweeps through long left-hand and right-hand bends around the foot of grassy hills. Sponsor boards pass along the way: glowing black-and-grey checkered \"VELTRA RACING\" billboards and blue-and-yellow hoardings on steel posts reading \"NOVAFUEL\" in bold blue capitals, with small red signs on steel scaffold towers, lone trees on the hillsides, and tall walls of dense dark woodland beneath the cobalt sky. White floodlight pools reveal grass, rail ribs, road texture, and tree edges against the surrounding blue shadows. <Subject 2> runs far ahead, pulling away and shrinking into a tiny distant car that drops out of view over crests or around far curves and reappears as a small speck on the distant road. <Subject 1> holds the lower center, swaying slightly on straights, tipping into bends with its tires scrubbing as the view swings, and settling its suspension through dips. The paint, liveries, billboards, reflective asphalt, twilight sky, and trackside lighting stay exactly as <Picture 1> shows them. The raspy engine rises through the gears with gear-shift barks and tire scrub in the bends over quiet evening insects; no speech is heard, and no text other than the existing signs and liveries appears on screen.\n\noverall_soundscape:\nA loud, raspy turbocharged four-cylinder race engine dominates throughout, rising in pitch through each gear, with sharp gear-shift barks, turbo flutter and exhaust crackle on each lift, the hiss of slick tires on asphalt with a light scrub as the car turns, steady wind rush over the body, and the fainter drone of the rival car's engine ahead; underneath lies a quiet rural twilight ambience of subdued insects and a soft breeze through the grass and trees, with a faint electrical hum near the trackside floodlights. There is no speech, no voice, and no crowd noise.\n\nnon_diegetic_music:\nN/A",
+    "backbone": "backbone/1008b_step224_backbone_ema_merged.safetensors"
+  },
+  "default_example": "B10_e-track-3_bluehour"
+}

audio_vae/model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:37dddc2f3e6d5d5139d823d5ea283bbf304dadcb885b1ccda818aa13dade5ea2
+size 605429308

configs/environment-tested.json

@@ -0,0 +1,22 @@
+{
+  "python": "3.11",
+  "torch": "2.9.1+cu128",
+  "triton": "3.5.1",
+  "transformers": "4.57.3",
+  "diffusers": "0.38.0",
+  "accelerate": "1.14.0",
+  "numpy": "2.3.5",
+  "Pillow": "11.3.0",
+  "PyYAML": "6.0.3",
+  "safetensors": "0.8.0",
+  "einops": "0.8.2",
+  "tabulate": "0.10.0",
+  "omegaconf": "2.3.1",
+  "flash-attn": "2.8.4+g0251105a2fb1",
+  "magi-attention": "1.1.1",
+  "nvidia-cutlass-dsl": "4.6.2",
+  "peft": "0.18.0",
+  "av": "18.1.0",
+  "timm": "0.6.13",
+  "node": "22.20.0"
+}

configs/runtime.json

@@ -0,0 +1,541 @@
+{
+  "schema": 1,
+  "backend": "h3",
+  "host": "127.0.0.1",
+  "port": 8765,
+  "max_pending_frames": 48,
+  "max_body_bytes": 12582912,
+  "output_queue_chunks": 2,
+  "session_idle_seconds": 120,
+  "output": {
+    "fps": 24,
+    "height": 768,
+    "width": 1344
+  },
+  "reference": {
+    "height": 480,
+    "width": 832
+  },
+  "warmup_rounds": 6,
+  "inference": {
+    "seed": 20260830,
+    "diffusion": {
+      "sampling_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.sampling.trailing",
+        "class_name": "TrailingSamplingTimesteps",
+        "args": {
+          "T": 1,
+          "num_sampling_steps": 2,
+          "shift": 6
+        }
+      },
+      "audio_sampling_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.sampling.trailing",
+        "class_name": "TrailingSamplingTimesteps",
+        "args": {
+          "T": 1,
+          "num_sampling_steps": 2,
+          "shift": 1.5
+        }
+      },
+      "schedule": {
+        "module": "dev.yanzuolu.common.diffusion.schedule.lerp",
+        "class_name": "LinearInterpolationSchedule",
+        "args": {
+          "T": 1,
+          "pred_type": "x_0"
+        }
+      },
+      "sampler": {
+        "module": "dev.yanzuolu.common.diffusion.sampler.ddim",
+        "class_name": "DDIMSampler",
+        "args": {}
+      },
+      "fake_schedule": {
+        "module": "dev.yanzuolu.common.diffusion.schedule.lerp",
+        "class_name": "LinearInterpolationSchedule",
+        "args": {
+          "T": 1,
+          "pred_type": "x_0"
+        }
+      },
+      "fake_training_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.training.uniform",
+        "class_name": "UniformTrainingTimesteps",
+        "args": {
+          "T": 1,
+          "shift": 6
+        }
+      },
+      "audio_fake_training_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.training.uniform",
+        "class_name": "UniformTrainingTimesteps",
+        "args": {
+          "T": 1,
+          "shift": 1.5
+        }
+      },
+      "score_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.training.uniform",
+        "class_name": "UniformTrainingTimesteps",
+        "args": {
+          "T": 1,
+          "shift": 6
+        }
+      },
+      "audio_score_timesteps": {
+        "module": "dev.yanzuolu.common.diffusion.timestep.training.uniform",
+        "class_name": "UniformTrainingTimesteps",
+        "args": {
+          "T": 1,
+          "shift": 1.5
+        }
+      }
+    },
+    "distributed": {
+      "up_size": [
+        1,
+        8
+      ]
+    },
+    "data": {
+      "args": {
+        "tokenizer_path": "asset://tokenizer",
+        "num_frames": 107,
+        "chunk_size": 2,
+        "fps": 24,
+        "height": 768,
+        "width": 1344,
+        "reference_height": 480,
+        "reference_width": 832,
+        "video_latent_channels": 24,
+        "audio_latent_channels": 32,
+        "spatial_vae_stride": 16,
+        "sink_size": 2,
+        "window_size": 2,
+        "bootstrap_size": 7,
+        "merge_single_frame_units": true,
+        "audio_lookahead_latents": 29,
+        "audio_right_lookahead_latents": 0,
+        "max_seqlen": 40960,
+        "max_seqlen_per_sample": 40960,
+        "max_retries": 5,
+        "sync_group_size": 1,
+        "text_dropout": 0
+      }
+    },
+    "meta_model": {
+      "teacher_streaming": {
+        "sink_size": 4,
+        "window_size": 5
+      },
+      "student_cfg_fitting": false,
+      "fake_cfg_fitting": true,
+      "teacher_cfg_fitting": false,
+      "cfg_fitting_guidance": {
+        "anchors": "guided",
+        "branches": [
+          {
+            "name": "null",
+            "drop": [
+              "text",
+              "reference"
+            ]
+          },
+          {
+            "name": "text_only",
+            "drop": [
+              "reference"
+            ]
+          }
+        ],
+        "stages": [
+          {
+            "branch": "null",
+            "scale": 1.5
+          },
+          {
+            "branch": "text_only",
+            "scale": 3
+          }
+        ]
+      },
+      "teacher_guidance_scale": [
+        1,
+        1
+      ],
+      "fake_loss_type": "x_0",
+      "fake_grad_enabled": false,
+      "real_grad_enabled": false,
+      "fake_use_trajectory": true,
+      "dmd_loss": {
+        "type": "dmd",
+        "norm_clip_min": 1e-05,
+        "phuber_c": 0.001,
+        "alpha": 1
+      },
+      "qwen_visual_context": true,
+      "qwen_reference_video": false,
+      "selective_video_encoding": false,
+      "qwen_processor_path": "asset://qwen_processor",
+      "audio_loss_weight": 1,
+      "bootstrap_loss_weight": 1,
+      "first_frame_loss_weight": 1,
+      "continuation_loss_weight": 1,
+      "separate_reference_rope": true,
+      "fixed_window_rope": true,
+      "keep_sink_reference": true,
+      "keep_negative_reference": true,
+      "loss_weighting": "uniform"
+    },
+    "models": {
+      "backbone": {
+        "module": "dev.yanzuolu.projects.minimax_h3.modeling.build",
+        "class_name": "MiniMaxH3CausalX0DiTSP",
+        "meta_init": true,
+        "args": {
+          "hidden_size": 5376,
+          "num_layers": 50,
+          "token_refiner_num_layers": 2,
+          "num_attention_heads": 56,
+          "attention_head_dim": 128,
+          "ffn_hidden_size": 14336,
+          "latents_dim": 24,
+          "audio_latents_dim": 32,
+          "patch_size": [
+            1,
+            2,
+            2
+          ],
+          "text_dim": 5120,
+          "timestep_input_dim": 256,
+          "time_embed_hidden_size": 5376,
+          "time_embed_dim": 2688,
+          "adaln_out_features": 96768,
+          "final_adaln_out_features": 10752,
+          "rope_inv_freq_len": 16,
+          "norm_eps": 1e-05,
+          "qk_norm_eps": 1e-05,
+          "final_norm_eps": 1e-05
+        },
+        "runtime": {
+          "training": false,
+          "requires_grad": false,
+          "param_dtype": "bfloat16"
+        },
+        "placement": {
+          "device": "cuda"
+        },
+        "weight": {
+          "path": "asset://backbone",
+          "strict": true,
+          "assign": true
+        }
+      },
+      "text_encoder": {
+        "module": "dev.yanzuolu.projects.minimax_h3_videoref.modeling.ref2va_encoder",
+        "class_name": "build_ref2va_encoder",
+        "meta_init": true,
+        "args": {
+          "pretrained_model_name_or_path": "asset://qwen_model"
+        },
+        "runtime": {
+          "training": false,
+          "requires_grad": false,
+          "param_dtype": "bfloat16"
+        },
+        "placement": {
+          "weight_dtype": "bfloat16",
+          "fsdp": {
+            "wrap_modules": [
+              "Qwen3VLTextDecoderLayer",
+              "Qwen3VLVisionBlock"
+            ],
+            "param_dtype": "bfloat16",
+            "reduce_dtype": "float32",
+            "shard_size": 4,
+            "cpu_offload": true
+          },
+          "plugins": [
+            {
+              "module": "dev.yanzuolu.common.plugin.dcp_weights",
+              "class_name": "ShardedDCPWeights",
+              "path": "asset://qwen_dcp"
+            }
+          ]
+        }
+      },
+      "video_vae": {
+        "module": "dev.yanzuolu.projects.minimax_h3.modeling.taeh3_native_streaming",
+        "class_name": "MiniMaxH3NativeStreamingTAE",
+        "meta_init": false,
+        "args": {
+          "parallel_encode": false,
+          "parallel_decode": false
+        },
+        "weight": {
+          "path": "asset://tae",
+          "strict": true,
+          "assign": false
+        },
+        "runtime": {
+          "training": false,
+          "requires_grad": false,
+          "param_dtype": "float16",
+          "plugins": [
+            {
+              "module": "dev.yanzuolu.common.plugin.autocast",
+              "class_name": "AutocastNoGradWrapper",
+              "functions": [
+                "encode_videos",
+                "encode_images",
+                "decode_base"
+              ],
+              "grad_enabled": false,
+              "autocast": {
+                "enabled": true,
+                "dtype": "float16"
+              }
+            }
+          ]
+        },
+        "placement": {
+          "weight_dtype": "float32"
+        }
+      },
+      "video_decoder": {
+        "module": "causal_vit_codec",
+        "class_name": "CausalViTVideoDecoder",
+        "meta_init": false,
+        "args": {
+          "student_weights": "asset://causal_decoder",
+          "decoder_config": {
+            "decoder_kwargs": {
+              "dim_head": 64,
+              "ffn_activation_fn": "silu",
+              "ffn_use_gated": true,
+              "heads": 32,
+              "norm_affine": true,
+              "norm_type": "rms_norm",
+              "num_layers": 24,
+              "qk_norm_affine": false,
+              "qk_norm_type": "rms_norm",
+              "rope_dim_ratio": 0.75,
+              "rope_theta": 100,
+              "patch_size": 16,
+              "patch_size_t": 4,
+              "t_causal": false,
+              "in_channels": 24,
+              "out_channels": 3
+            },
+            "embed_dim": 24,
+            "keep_layers": [
+              0,
+              1,
+              2,
+              3,
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+            "latents_mean": [
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+          "param_dtype": "float32"
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+        "placement": {
+          "weight_dtype": "float32"
+        }
+      },
+      "audio_vae": {
+        "module": "dev.yanzuolu.projects.minimax_h3.modeling.build",
+        "class_name": "MiniMaxH3AudioVAE",
+        "meta_init": false,
+        "args": {
+          "attn_proj": true,
+          "decoder_dim": 1024,
+          "decoder_rates": [
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+            5,
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+}

inventory.json

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 {
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qwen_model/chat_template.json

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+{
+    "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
+}

qwen_model/config.json

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+{
+  "architectures": [
+    "Qwen3VLForConditionalGeneration"
+  ],
+  "image_token_id": 151655,
+  "model_type": "qwen3_vl",
+  "text_config": {
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+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 25600,
+    "max_position_embeddings": 262144,
+    "model_type": "qwen3_vl_text",
+    "num_attention_heads": 64,
+    "num_hidden_layers": 64,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        24,
+        20,
+        20
+      ],
+      "rope_type": "default"
+    },
+    "rope_theta": 5000000,
+    "use_cache": true,
+    "vocab_size": 151936
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.0.dev0",
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+    "model.visual.merger.linear_fc2.weight": "model-00014-of-00014.safetensors",
+    "model.visual.merger.norm.bias": "model-00014-of-00014.safetensors",
+    "model.visual.merger.norm.weight": "model-00014-of-00014.safetensors",
+    "model.visual.patch_embed.proj.bias": "model-00014-of-00014.safetensors",
+    "model.visual.patch_embed.proj.weight": "model-00014-of-00014.safetensors",
+    "model.visual.pos_embed.weight": "model-00014-of-00014.safetensors"
+  }
+}

qwen_model/preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

qwen_model/tokenizer_config.json

@@ -0,0 +1,246 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>",
+    "<d>",
+    "</d>",
+    "<|cutoff|>",
+    "<|lyrics_start|>",
+    "<|lyrics_end|>",
+    "<|caption_start|>",
+    "<|caption_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 262144,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

qwen_model/video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}

qwen_processor/chat_template.json

@@ -0,0 +1,3 @@
+{
+    "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
+}

qwen_processor/preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

qwen_processor/tokenizer_config.json

@@ -0,0 +1,246 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>",
+    "<d>",
+    "</d>",
+    "<|cutoff|>",
+    "<|lyrics_start|>",
+    "<|lyrics_end|>",
+    "<|caption_start|>",
+    "<|caption_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' }}\n        {%- if messages[0].content is string %}\n            {{- messages[0].content }}\n        {%- else %}\n            {%- for content in messages[0].content %}\n                {%- if 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- for message in messages %}\n    {%- if message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content_item in message.content %}\n                {%- if 'text' in content_item %}\n                    {{- content_item.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and message.content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {%- if message.content is string %}\n            {{- message.content }}\n        {%- else %}\n            {%- for content in message.content %}\n                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}\n                    <|vision_start|><|image_pad|><|vision_end|>\n                {%- elif content.type == 'video' or 'video' in content %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}\n                    <|vision_start|><|video_pad|><|vision_end|>\n                {%- elif 'text' in content %}\n                    {{- content.text }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 262144,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

qwen_processor/video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}

tae/taeh3_official.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af92965c2d7986a89a757e7cccd26f9eeeff0c3f0d5495eb168aeb2d6d9be9ba
+size 22745717