XGENlabs/XGEN-JING
image-text-to-video model by XGENlabs
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
XGEN-JING: An Egocentric Interactive Experience Model XGEN Team We present XGEN-JING, an egocentric interactive experience model built on MiniMax-H3. Given actions, reference images, and observation history, JING generates first-person video and audio for navigation, object interaction, and conversation. keyboard-controlled movement. conversations with text, with video and audio generated together. 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. 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. SGLang runtime and validated CUDA versions Install SGLang at commit 95140a7b0c9fc2f87a2a6cf6f6f0df8640a73174 separately. Keep the Diffusers revision pinned in requirements.txt; SGLang's diffusion extra pins a different version. The validated stack…
Read the full model card ↗ · Preview checked 2026-09-20T09:15:42.651Z
Inside the original model card — Document outline
- 📋 Release Plan
- 🚀 Quick Start
- 1. Installation
- 2. Model weights
- 3. Inference
- Prompt skills
- 🤝 Acknowledgments
- License
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Model overview
XGENlabs/XGEN-JING is a image-text-to-video model repository published by XGENlabs on Hugging Face. The source reports the diffusers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-video
- Library
- diffusers
- Recent downloads (30 days)
- 2
- Cumulative likes
- 150
- Hugging Face trending score
- 127
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-09-16T10:02:50.000Z
- Last modified
- 2026-09-20T09:23:32.000Z
Compatibility and lineage
Reported languages: en, zh
Reported base models: MiniMaxAI/MiniMax-H3
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:47.722Z. Daily imports are snapshots, not real-time monitoring.
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