Upload README.md

README.md

@@ -124,44 +124,6 @@ image = pipe(
 image.save("moss_image.png")
 ```
 
-## Reference images
-
-MOSS-Image can also take reference images, through the vision part of its Qwen3.5 text encoder. The model wasn't trained for this: references guide the content, style and layout of the image, not exact pixels or identity. Load the `reference` workflow and pass the images with `reference_images`:
-
-```python
-import torch
-from diffusers import ModularPipelineBlocks
-from diffusers.utils import load_image
-
-
-blocks = ModularPipelineBlocks.from_pretrained(
-    "OzzyGT/moss_image_custom_blocks",
-    trust_remote_code=True,
-    components_repo="OzzyGT/MOSS_Image_SFT_diffusers",
-    trust_components_code=True,
-)
-pipe = blocks.init_pipeline()
-pipe.load_components(workflow="reference", dtype={"default": torch.bfloat16, "vae": torch.float32})
-pipe.to("cuda")
-
-reference = load_image(
-    "https://huggingface.co/datasets/OzzyGT/diffusers-examples/resolve/main/krea2_reference/20260907154202_edit_image_0.png"
-)
-
-image = pipe(
-    prompt="photo",
-    reference_images=reference,
-    num_inference_steps=28,
-    height=1024,
-    width=1024,
-    generator=torch.Generator("cuda").manual_seed(42),
-    output="images",
-)[0]
-image.save("moss_image_reference.png")
-```
-
-`reference_max_pixels` (default 1024 x 1024) sets how large each reference is for the vision encoder. To load only what text-to-image needs, without the vision encoder, use `workflow="text2image"` as in the sample above.
-
 ## License
 
 This model is released under the [Apache-2.0 license](LICENSE), the same as the original.