Add model card (run prod-20260407)

README.md

@@ -1,3 +1,121 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+  - Qwen/Qwen-Image-2512
+  - Qwen/Qwen-Image-Edit-2511
+  - Qwen/Qwen-Image
+tags:
+  - image-generation
+  - qwen
+  - mmdit
+  - abliterated
+  - quantized
+  - rocm
+language:
+  - en
+library_name: diffusers
+pipeline_tag: text-to-image
+---
+
+# Qwen-Image-1.9
+
+A merged, abliterated, and quantized derivative of the Qwen-Image 20B MMDiT family.
+
+> **Run ID:** `prod-20260407`
+> **Created:** 2026-04-07T18:59:37+00:00
+
+## Architecture
+
+| Property | Value |
+| --- | --- |
+| Base family | Qwen-Image (MMDiT 20B) |
+| Text encoder | Qwen2.5-VL |
+| VAE | RGB-VAE |
+| RoPE | 2D |
+| Backbone parameters | ~20B |
+| License | Apache-2.0 |
+
+## Source Models
+
+| Alias | Model | Role | License |
+| --- | --- | --- | --- |
+| `qwen-image-2512` | [Qwen/Qwen-Image-2512](https://huggingface.co/Qwen/Qwen-Image-2512) | foundation | Apache-2.0 |
+| `qwen-image-base` | [Qwen/Qwen-Image](https://huggingface.co/Qwen/Qwen-Image) | ancestry-base | Apache-2.0 |
+| `qwen-image-edit-2511` | [Qwen/Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) | edit-donor | Apache-2.0 |
+| `qwen-image-layered` | [Qwen/Qwen-Image-Layered](https://huggingface.co/Qwen/Qwen-Image-Layered) | layer-logic-donor | Apache-2.0 |
+
+## Research Method
+
+### 1. Delta-Edit Merge
+
+The edit capability is transferred to the foundation model via a controlled
+delta injection:
+
+```
+edit_delta = Qwen-Image-Edit-2511 − Qwen-Image (delta base)
+merged     = Qwen-Image-2512 + 0.35 × edit_delta
+```
+
+Only MMDiT backbone tensors are blended. Text encoder, VAE, and RoPE
+components are passed through from the foundation checkpoint unchanged.
+
+- **Strategy:** `slerp`
+- **Blend coefficient:** `0.35`
+- **Foundation:** `Qwen/Qwen-Image-2512`
+- **Excluded subsystems:** text_encoder, vae, rope
+
+### 2. Abliteration (Refusal-Direction Removal)
+
+Refusal-direction vectors are identified in the residual stream and
+projected out of target weight matrices using a norm-preserving
+orthogonal projection:
+
+```
+W′ = W − scale × (W @ r̂) ⊗ r̂    (norm-preserving variant)
+```
+
+- **Target layers:** 18+ (attention o_proj + MLP down_proj)
+- **Scale:** 1.0
+- **Mode:** norm-preserving (preserves weight magnitude distribution)
+- Recipe: `stage-3-abliteration.yaml`
+
+### 3. Quantization
+
+| Kind | Path |
+| --- | --- |
+| `quant_config` | `quant-config.json` |
+
+- **GGUF targets:** Q4_K_M, IQ4_XS (with importance-matrix)
+- **EXL2 target:** 4.0 bpw
+- **Runtime:** vLLM-Omni (ROCm), ExLlamaV2
+
+## Hardware
+
+- **GPU:** AMD Instinct MI300X — 192 GB HBM3 VRAM
+- **ROCm:** 7.2.0
+- **Precision:** bf16 (merge + abliterate), quantized (deployment)
+
+## Usage
+
+```python
+from diffusers import DiffusionPipeline
+import torch
+
+pipe = DiffusionPipeline.from_pretrained(
+    "ThirdMiddle/Qwen-Image-1.9",
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+)
+pipe = pipe.to("cuda")
+
+image = pipe(
+    "a photorealistic portrait of an astronaut on Mars at sunrise",
+    num_inference_steps=30,
+    guidance_scale=4.0,
+).images[0]
+image.save("output.png")
+```
+
+## License
+
+Apache-2.0 — inherited from all source models.