Update README.md

README.md

@@ -1,31 +1,193 @@
 ---
 license: apache-2.0
 library_name: diffusers
+pipeline_tag: text-to-video
+
 tags:
 - arachne
 - nullxes
-- text-to-video
-- video-generation
 - foundation
-pipeline_tag: text-to-video
+- video-generation
+- text-to-video
+- diffusion-transformer
+- realtime-runtime
+- enterprise-ai
+- multimodal
+- sovereign-ai
+
 datasets:
 - MagistrTheOne/ARACHNE-FOUNDATION-DATA-SMOKE
 ---
 
 # ARACHNE-FOUNDATION-50B
 
-NULLXES ARACHNE foundation video DiT checkpoint (depth 178).
+> 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:
 
-**Core team:** NULLXES LLC — CEO [@MagistrTheOne](https://huggingface.co/MagistrTheOne) — ceo@nullxes.com
+- [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.
+
+---
 
-## Status
+# Important Notice
 
-Surgical depth init from [ARACHNE-X-ULTRA-VIDEO](https://huggingface.co/MagistrTheOne/ARACHNE-X-ULTRA-VIDEO). Continue pretrain required before production serving.
+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
+
+---
 
-## Files
+# Final Note
 
-Safetensors shards and config.json at repository root (Diffusers DiT layout).
+ARACHNE-FOUNDATION is not being developed as a consumer entertainment model.
 
-## Training data
+Its direction is toward:
 
-[ARACHNE-FOUNDATION-DATA-SMOKE](https://huggingface.co/datasets/MagistrTheOne/ARACHNE-FOUNDATION-DATA-SMOKE)
+> realtime operational AI infrastructure for next-generation digital workforce systems.