| license: apache-2.0 | |
| library_name: diffusers | |
| pipeline_tag: text-to-video | |
| tags: | |
| - arachne | |
| - nullxes | |
| - foundation | |
| - video-generation | |
| - text-to-video | |
| - diffusion-transformer | |
| - realtime-runtime | |
| - enterprise-ai | |
| - multimodal | |
| - sovereign-ai | |
| datasets: | |
| - MagistrTheOne/ARACHNE-FOUNDATION-DATA-SMOKE | |
| # ARACHNE-FOUNDATION-50B | |
| > Foundation-scale video diffusion backbone engineered for the next generation of realtime AI systems. | |
| ARACHNE-FOUNDATION-50B is an experimental large-scale DiT foundation checkpoint developed by NULLXES as part of the ARACHNE runtime ecosystem. | |
| This repository represents an early foundation transition stage of the ARACHNE lineage: | |
| from operational realtime avatar/video systems toward a sovereign large-scale multimodal video backbone optimized for realtime inference, streaming generation, identity stability, and future native audio-video architectures. | |
| --- | |
| # Overview | |
| ARACHNE-FOUNDATION-50B is currently a: | |
| - depth-expanded initialization checkpoint | |
| - architectural research foundation | |
| - pretraining-ready DiT topology | |
| - runtime-compatible experimental backbone | |
| This release is **NOT** a fully trained production model. | |
| The checkpoint was surgically expanded from: | |
| - [ARACHNE-X-ULTRA-VIDEO](https://huggingface.co/MagistrTheOne/ARACHNE-X-ULTRA-VIDEO) | |
| using internal topology scaling procedures and initialization surgery. | |
| --- | |
| # Current Status | |
| | Component | Status | | |
| |---|---| | |
| | Depth expansion | ✅ Complete | | |
| | Diffusers compatibility | ✅ Complete | | |
| | Safetensors export | ✅ Complete | | |
| | Smoke forward validation | ✅ Complete | | |
| | Runtime compatibility | ✅ Complete | | |
| | Full pretraining | ⏳ Pending | | |
| | Native audio generation | ⏳ Planned | | |
| | Benchmark evaluation | ⏳ Pending | | |
| | Production deployment | ❌ Not ready | | |
| --- | |
| # Architecture | |
| | Property | Value | | |
| |---|---| | |
| | Model Type | Diffusion Transformer (DiT) | | |
| | Scale | ~50B parameters | | |
| | Depth | 178 transformer blocks | | |
| | Format | Diffusers | | |
| | Weights | Safetensors | | |
| | Runtime Target | ARACHNE Runtime Stack | | |
| | Intended Direction | Realtime multimodal generation | | |
| --- | |
| # Design Philosophy | |
| Unlike cinematic-first video generators, ARACHNE-FOUNDATION is being developed around: | |
| - realtime inference architecture | |
| - operational latency constraints | |
| - streaming generation | |
| - identity persistence | |
| - chunk-aware generation | |
| - deterministic runtime behavior | |
| - future digital employee systems | |
| The long-term goal is not only high-quality video synthesis, but stable realtime operational generation inside enterprise-grade AI runtime systems. | |
| --- | |
| # Important Notice | |
| This repository currently contains an initialization-stage checkpoint. | |
| The released weights: | |
| - have NOT undergone large-scale continuation pretraining | |
| - are NOT benchmarked against production-grade video models | |
| - should NOT be considered final quality weights | |
| - are intended for architecture research, runtime experimentation, and future scaling work | |
| At this stage, this repository should be viewed as: | |
| > a foundation topology transition checkpoint, not a finished frontier model. | |
| --- | |
| # Training Data | |
| Current smoke/evaluation dataset: | |
| - [ARACHNE-FOUNDATION-DATA-SMOKE](https://huggingface.co/datasets/MagistrTheOne/ARACHNE-FOUNDATION-DATA-SMOKE) | |
| Future large-scale pretraining datasets are not yet publicly released. | |
| --- | |
| # Runtime Ecosystem | |
| ARACHNE-FOUNDATION is part of the broader NULLXES runtime ecosystem: | |
| | Layer | Role | | |
| |---|---| | |
| | ASTERIAS | Deterministic reasoning layer | | |
| | ARACHNE-X | Realtime avatar/video runtime | | |
| | FOUNDATION | Large-scale backbone research | | |
| | Session Workers | Operational orchestration | | |
| | NULLXES | Enterprise AI infrastructure | | |
| --- | |
| # Repository Structure | |
| ```text | |
| /config.json | |
| /diffusion_pytorch_model-*.safetensors | |
| /model_index.json | |
| /README.md | |
| ``` | |
| --- | |
| # Roadmap | |
| ## Phase 1 — Foundation Transition | |
| - topology scaling | |
| - runtime stabilization | |
| - compatibility verification | |
| ## Phase 2 — Foundation Pretraining | |
| - temporal coherence learning | |
| - motion priors | |
| - identity consistency | |
| - multimodal alignment | |
| ## Phase 3 — Realtime Optimization | |
| - chunk-aware distillation | |
| - low-latency inference | |
| - KV-cache optimization | |
| - streaming-native generation | |
| ## Phase 4 — Native Multimodal Runtime | |
| - integrated audio/video generation | |
| - realtime duplex interaction | |
| - operational digital employee systems | |
| --- | |
| # Authors | |
| **NULLXES LLC** | |
| CEO & Architect: [@MagistrTheOne](https://huggingface.co/MagistrTheOne) | |
| Contact: | |
| - ceo@nullxes.com | |
| - Telegram: @MagistrTheOne | |
| --- | |
| # Final Note | |
| ARACHNE-FOUNDATION is not being developed as a consumer entertainment model. | |
| Its direction is toward: | |
| > realtime operational AI infrastructure for next-generation digital workforce systems. |
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