Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+tags:
+  - lora
+  - video-generation
+  - wan
+  - wan-2.1
+  - wan-2.2
+  - training
+  - text-to-video
+  - image-to-video
+  - diffusion-transformer
+---
+
+# Flimmer
+
+Video LoRA training toolkit for diffusion transformer models. Built by [Alvdansen Labs](https://github.com/alvdansen).
+
+Full pipeline from raw footage to trained LoRA checkpoint — scene detection, captioning, 
+dataset validation, latent pre-encoding, and training. Currently supports WAN 2.1 and 
+WAN 2.2 (T2V and I2V).
+
+Early release. Building in the open.
+
+## What it covers
+
+- **Video ingestion** — scene detection, clip splitting, fps/resolution normalization
+- **Captioning** — Gemini and Replicate backends
+- **CLIP-based triage** — find clips matching a reference person or concept in large footage sets
+- **Dataset validation** — catch missing captions, resolution mismatches, and format issues before spending GPU time
+- **Latent pre-encoding** — VAE + T5 cached to disk so training doesn't repeat encoding every epoch
+- **Training** — LoRA training with checkpoint resume, W&B logging, and in-training video sampling
+
+## Phased training
+
+The standout feature. Break a training run into sequential stages — each with its own 
+learning rate, epoch budget, and dataset — while the LoRA checkpoint carries forward 
+automatically between phases.
+
+Use it for curriculum training (simple compositions before complex motion) or for 
+WAN 2.2's dual-expert MoE architecture, where the high-noise and low-noise experts 
+can be trained with specialized hyperparameters after a shared base phase. 
+MoE expert specialization is experimental — hyperparameters are still being validated.
+
+## Standalone data tools
+
+The data preparation tools output standard formats compatible with any trainer — 
+kohya, ai-toolkit, or anything else. You don't need to use Flimmer's training loop 
+to benefit from the captioning, triage, and validation tooling.
+
+## Model support
+
+| Model | T2V | I2V |
+|---|---|---|
+| WAN 2.1 | ✅ | ✅ |
+| WAN 2.2 | ✅ | ✅ |
+| LTX | 🔜 | 🔜 |
+
+Image training is out of scope — ai-toolkit handles it thoroughly and there's no point 
+duplicating it. Flimmer is video-native.
+
+## Installation & docs
+
+Full installation instructions, config reference, and guides are on GitHub:
+
+**[github.com/alvdansen/flimmer-trainer](https://github.com/alvdansen/flimmer-trainer)**
+
+Supports RunPod and local GPU (tested on A6000/48GB).