xgen-jing bidirectional demo

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LICENSE

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NOTICE

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+XGEN-JING
+Copyright 2026 XGEN Team. All rights reserved.
+XGEN-JING code and model modifications are released under the MiniMax H3
+Community License Agreement; see LICENSE.
+
+MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
+https://huggingface.co/MiniMaxAI/MiniMax-H3
+
+This demo uses MiniMax-H3 components from Hugging Face Diffusers.
+Selected transformer-forward and attention conventions are adapted from:
+https://github.com/huggingface/diffusers/tree/abc5e9bf71fd38f53cd471bc3acaa84bc5ecbfdc
+Copyright 2026 The MiniMax and HuggingFace Teams. All rights reserved.
+These upstream portions retain their Apache License, Version 2.0;
+see LICENSE.apache-2.0. The adaptations add JING controls and inference support.
+
+JING Flash builds upon the FlashGen four-step model published by Beidouqixing:
+https://huggingface.co/Beidouqixing/minimax-h3-4step-lora-flashgen
+The upstream release is published under Apache-2.0; see LICENSE.apache-2.0.
+JING Flash includes model modifications by XGEN Team. The resulting H3 model
+derivative is subject to the MiniMax H3 Community License Agreement.
+
+The runtime calls SGLang's public checkpoint and sharded-inference loader:
+https://github.com/sgl-project/sglang/tree/95140a7b0c9fc2f87a2a6cf6f6f0df8640a73174
+SGLang is distributed under Apache-2.0. Its source is not vendored here.

README.md

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+---
+license: other
+license_name: minimax-h3-community-license-agreement
+license_link: LICENSE
+language:
+  - en
+  - zh
+base_model: MiniMaxAI/MiniMax-H3
+library_name: diffusers
+pipeline_tag: image-text-to-video
+tags:
+  - xgen-jing
+  - world-model
+  - egocentric
+  - video-generation
+  - audio-video-generation
+---
+
+<div align="center">
+  <video width="100%" controls playsinline preload="none" poster="https://huggingface.co/XGENlabs/XGEN-JING/resolve/main/assets/xgen-jing-cover.jpg?v=5d27805a7323">
+    <source src="https://huggingface.co/XGENlabs/XGEN-JING/resolve/main/assets/xgen-jing-demo.mp4?v=43fc8e7436a0" type="video/mp4">
+    <a href="https://huggingface.co/XGENlabs/XGEN-JING/resolve/main/assets/xgen-jing-demo.mp4?v=43fc8e7436a0">Watch the demo</a>
+  </video>
+</div>
+
+<h1 align="center">
+  XGEN-JING: An Egocentric<br>
+  Interactive Experience Model
+</h1>
+<p align="center">XGEN Team</p>
+
+<p align="center">
+  <a href="https://github.com/XGEN-Labs/XGEN-JING"><img src="https://img.shields.io/badge/GitHub-XGEN--JING-181717?logo=github&amp;logoColor=white" alt="GitHub"></a>
+  <a href="https://huggingface.co/XGENlabs/XGEN-JING"><img src="https://img.shields.io/badge/Hugging_Face-Models-FFD21E?logo=huggingface&amp;logoColor=black" alt="Hugging Face"></a>
+  <a href="https://xgenlabs.ai/gallery.html"><img src="https://img.shields.io/badge/Gallery-XGEN--JING-2563EB" alt="Gallery"></a>
+  <a href="https://xgenlabs.ai/research.html"><img src="https://img.shields.io/badge/Blog-XGEN%20Labs-F97316" alt="Blog"></a>
+  <img src="https://img.shields.io/badge/arXiv-Coming_Soon-B31B1B?logo=arxiv&amp;logoColor=white" alt="arXiv: Coming Soon">
+</p>
+
+---
+
+We present **XGEN-JING**, an egocentric interactive experience model built on
+[MiniMax-H3](https://github.com/MiniMax-AI/MiniMax-H3). Given actions, reference
+images, and observation history, JING generates first-person video and audio for
+navigation, object interaction, and conversation.
+
+- **Camera control.** Explore everyday places and imagined worlds through
+  keyboard-controlled movement.
+- **Interaction and dialogue.** Guide object interactions and character
+  conversations with text, with video and audio generated together.
+- **Reference conditioning.** Combine character, object, and scene images to
+  compose an experience and explore different actions from the same starting point.
+
+This release provides **four-step bidirectional inference**, example cases, and
+**Prompt skills**. The causal model and technical report are coming soon.
+
+## 📋 Release Plan
+
+- [x] **JING-Flash-v1** — Four-step bidirectional model.
+- [x] **Inference code and examples** — Camera controls, reference images, and joint audio/video generation.
+- [x] **[Prompt skills](https://github.com/XGEN-Labs/XGEN-JING/blob/main/prompt_skills/SKILL.md)** — Generate validated inference cases from stories and reference images.
+- [ ] **Causal model** — Coming soon.
+- [ ] **Technical report** — Coming soon.
+
+## 🚀 Quick Start
+
+### 1. Installation
+
+Use Python 3.12 and a compatible CUDA environment. The demo has been validated on
+**six H100 GPUs**: one for the text encoder, one for the video/audio VAEs, and four
+for the DiT with sequence parallelism. FlashAttention-4 is the default backend.
+
+```bash
+git clone https://github.com/XGEN-Labs/XGEN-JING.git
+cd XGEN-JING
+python3 -m pip install -r requirements.txt
+```
+
+<details>
+<summary>SGLang runtime and validated CUDA versions</summary>
+
+Install [SGLang](https://github.com/sgl-project/sglang/tree/95140a7b0c9fc2f87a2a6cf6f6f0df8640a73174)
+at commit `95140a7b0c9fc2f87a2a6cf6f6f0df8640a73174` separately. Keep the Diffusers
+revision pinned in `requirements.txt`; SGLang's diffusion extra pins a different
+version. The validated stack uses Torch 2.13.0+cu130, torchvision 0.28.0+cu130,
+Triton 3.7.1, FA4 4.0.0b26, and SGLang kernel 0.4.7+cu130 from the
+[CUDA 13 wheel index](https://sgl-project.github.io/whl/cu130/sglang-kernel/).
+
+</details>
+
+### 2. Model weights
+
+JING Flash is built upon
+[MiniMax-H3 Ref2VA](https://huggingface.co/MiniMaxAI/MiniMax-H3) and
+[FlashGen](https://huggingface.co/Beidouqixing/minimax-h3-4step-lora-flashgen)
+for a faster experience.
+
+The demo loads the **JING-Flash-v1 transformer** from
+[Hugging Face](https://huggingface.co/XGENlabs/XGEN-JING/tree/main/jing_flash_v1).
+The text encoder, tokenizer, processor, video/audio VAEs, and schedulers come from
+**Diffusers-format MiniMax-H3**.
+
+Required model files are downloaded automatically on first use and reused from the
+Hugging Face cache. Set `HF_HOME` to choose the cache location. No manual download
+or weight directory is required. Repository IDs are configured in
+[configs/base.yaml](https://github.com/XGEN-Labs/XGEN-JING/blob/main/configs/base.yaml).
+
+### 3. Inference
+
+```bash
+python3 demo_bidirection.py check_config=true
+bash demo.sh cases=examples/bakery_greeting.json
+```
+
+Results are saved to `examples/outputs/`.
+
+<details>
+<summary>Custom model paths and GPU selection</summary>
+
+```bash
+CUDA_VISIBLE_DEVICES=0,1,2,3,4,5 bash demo.sh \
+  model.h3=/path/to/MiniMax-H3 \
+  model.transformer=/path/to/XGEN-JING \
+  output.directory=/path/to/outputs
+```
+
+</details>
+
+<details>
+<summary>Write your own prompts and controls</summary>
+
+Start from [the bakery example](https://github.com/XGEN-Labs/XGEN-JING/blob/main/examples/bakery_greeting.json). Each case combines
+reference images with a sequence of prompts and controls. A prompt chunk uses one
+control entry per repeated slice:
+
+```json
+{
+  "prompt": "First-person view: approach the counter and greet the baker.",
+  "repeat": 3,
+  "control": ["w", "w,a", ""]
+}
+```
+
+`w/s/a/d` control forward/backward/left/right movement. `"w,a"` combines two keys
+in one slice; `""` applies no keys. Keep `control` the same length as `repeat`.
+With the default layout, `num_frames = 17 * sum(repeat) + 5`. Reference images
+are ordered and addressed as `<Picture 1>`, `<Picture 2>`, and so on, up to five.
+
+</details>
+
+### Prompt skills
+
+Use **[Prompt skills](https://github.com/XGEN-Labs/XGEN-JING/blob/main/prompt_skills/README.md)** to turn a story and reference images
+into a validated cases JSON file, ready to pass to `demo.sh`. It includes a
+standalone guide and supports a configurable Chat Completions API.
+
+## 🤝 Acknowledgments
+
+We thank the **[MiniMax-H3 team](https://github.com/MiniMax-AI/MiniMax-H3)** for
+opening their audio/video foundation model, and the
+**[FlashGen team](https://huggingface.co/Beidouqixing/minimax-h3-4step-lora-flashgen)**
+for their four-step acceleration work and model release.
+
+We also thank [Diffusers](https://github.com/huggingface/diffusers),
+[SGLang](https://github.com/sgl-project/sglang), and
+[FlashAttention](https://github.com/Dao-AILab/flash-attention) for their open-source
+infrastructure. See [NOTICE](https://github.com/XGEN-Labs/XGEN-JING/blob/main/NOTICE) for component attributions.
+
+## License
+
+XGEN-JING code and model weights are released under the
+[MiniMax H3 Community License Agreement](https://github.com/XGEN-Labs/XGEN-JING/blob/main/LICENSE). Third-party components retain
+their original licenses; see [NOTICE](https://github.com/XGEN-Labs/XGEN-JING/blob/main/NOTICE).

assets/xgen-jing-demo.mp4

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jing_flash_v1/LICENSE

@@ -0,0 +1,84 @@
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jing_flash_v1/LICENSE.apache-2.0

@@ -0,0 +1,201 @@
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jing_flash_v1/NOTICE

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+XGEN-JING
+Copyright 2026 XGEN Team. All rights reserved.
+XGEN-JING code and model modifications are released under the MiniMax H3
+Community License Agreement; see LICENSE.
+
+MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
+https://huggingface.co/MiniMaxAI/MiniMax-H3
+
+This demo uses MiniMax-H3 components from Hugging Face Diffusers.
+Selected transformer-forward and attention conventions are adapted from:
+https://github.com/huggingface/diffusers/tree/abc5e9bf71fd38f53cd471bc3acaa84bc5ecbfdc
+Copyright 2026 The MiniMax and HuggingFace Teams. All rights reserved.
+These upstream portions retain their Apache License, Version 2.0;
+see LICENSE.apache-2.0. The adaptations add JING controls and inference support.
+
+JING Flash builds upon the FlashGen four-step model published by Beidouqixing:
+https://huggingface.co/Beidouqixing/minimax-h3-4step-lora-flashgen
+The upstream release is published under Apache-2.0; see LICENSE.apache-2.0.
+JING Flash includes model modifications by XGEN Team. The resulting H3 model
+derivative is subject to the MiniMax H3 Community License Agreement.
+
+The runtime calls SGLang's public checkpoint and sharded-inference loader:
+https://github.com/sgl-project/sglang/tree/95140a7b0c9fc2f87a2a6cf6f6f0df8640a73174
+SGLang is distributed under Apache-2.0. Its source is not vendored here.

jing_flash_v1/config.json

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+{
+  "_class_name": "H3Transformer",
+  "_diffusers_version": "0.36.0.dev0",
+  "num_attention_heads": 56,
+  "attention_head_dim": 128,
+  "hidden_size": 5376,
+  "num_layers": 50,
+  "num_refiner_layers": 2,
+  "ffn_dim": 14336,
+  "in_channels": 24,
+  "audio_in_channels": 32,
+  "patch_size": [
+    1,
+    2,
+    2
+  ],
+  "text_dim": 5120,
+  "freq_dim": 256,
+  "time_embed_hidden_dim": 5376,
+  "time_embed_dim": 2688,
+  "rope_freq_dim": 16,
+  "rope_theta": 10000.0,
+  "norm_eps": 1e-05,
+  "qk_norm_eps": 1e-05,
+  "final_norm_eps": 1e-05,
+  "control_config": {
+    "enable": true,
+    "dim_in": 6,
+    "dim_out": 512
+  },
+  "attention_backend": "fa4"
+}

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