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README.md

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+---
+license: mit
+base_model:
+  - black-forest-labs/FLUX.2-klein-4B
+  - openbmb/MiniCPM5-1B
+  - black-forest-labs/FLUX.2-small-decoder
+tags:
+  - flux
+  - flux2
+  - distillation
+  - lora
+  - text-to-image
+  - diffusers
+library_name: diffusers
+pipeline_tag: text-to-image
+---
+
+# flux2tiny — Distilled FLUX.2-klein-4B with MiniCPM5-1B Text Encoder
+
+This repository contains the **trained adapter and LoRA weights** for flux2tiny,
+a distilled version of [FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B)
+that replaces the 4B-parameter Qwen3-4B text encoder with
+[MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B) (1.08B parameters).
+
+## What's in this repo
+
+| File | Size | Description |
+|:-----|:-----|:------------|
+| `adapter.safetensors` | ~23 MB | Projection adapter (3× Linear 1536→2560, concatenated to 7680) |
+| `transformer_lora/adapter_model.safetensors` | ~7.5 MB | PEFT LoRA weights (rank 16) for Flux2Transformer2DModel |
+| `transformer_lora/adapter_config.json` | ~1 KB | PEFT LoRA configuration |
+
+## Required base models (downloaded automatically)
+
+- [black-forest-labs/FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B) — Transformer backbone
+- [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B) — Student text encoder
+- [black-forest-labs/FLUX.2-small-decoder](https://huggingface.co/black-forest-labs/FLUX.2-small-decoder) — VAE decoder
+
+## Usage
+
+```python
+# Clone the code repo
+# git clone https://github.com/ElMiloPy/flux2tiny.git
+
+from pipeline import Flux2TinyPipeline
+
+pipe = Flux2TinyPipeline(
+    adapter_path="path/to/adapter.safetensors",
+    lora_path="path/to/transformer_lora",
+)
+
+image = pipe("A cat sitting on a windowsill at sunset", height=512, width=512)
+image.save("output.png")
+```
+
+Or via CLI:
+```bash
+python generate.py "A cat sitting on a windowsill at sunset" \
+    --adapter path/to/adapter.safetensors \
+    --lora path/to/transformer_lora \
+    --size 512x512
+```
+
+## Training details
+
+Trained via a 3-stage knowledge distillation pipeline:
+
+1. **Adapter pre-training** — MSE alignment between MiniCPM5-1B and Qwen3-4B hidden states
+2. **Teacher latent generation** — 15,000 latent-prompt pairs from the original FLUX.2 pipeline
+3. **Flow Matching LoRA distillation** — Joint training of adapter + transformer LoRA on teacher latents
+
+See [github.com/ElMiloPy/flux2tiny](https://github.com/ElMiloPy/flux2tiny) for full details.
+
+## License
+
+- **These weights**: MIT
+- **FLUX.2-klein-4B**: Apache 2.0
+- **MiniCPM5-1B**: Apache 2.0