Update README.md

README.md

@@ -9,7 +9,6 @@ library_name: diffusers
 tags:
 - text-to-image
 - image-editing
-- flux
 - diffusion-single-file
 - vae
 - decoder
@@ -19,15 +18,15 @@ tags:
 
 ![Comparison Panel](./comparison_panel.jpeg)
 
-`Rift.1-decoder` is a FLUX-compatible VAE decoder made for the Rift model line. It is designed as a **drop-in decoder component** for compatible FLUX.2-style Diffusers pipelines that use `AutoencoderKLFlux2`. The encoder path remains compatible with FLUX-style latent encoding, while the decoder has been trained as the Rift image reconstruction component.
+`Rift.1-decoder` is a VAE decoder made for the Rift model line. It is designed as a **drop-in decoder component** for compatible Diffusers image pipelines that use `AutoencoderKLFlux2`. The decoder has been trained as the Rift image reconstruction component.
 
 The exported Diffusers runtime class remains `AutoencoderKLFlux2` for loader compatibility. The model metadata identifies the architecture as `Rift1Decoder` with model type `rift1_decoder`.
 
 # **Key Features**
 
-1. **FLUX-compatible decoder interface** using `AutoencoderKLFlux2`.
+1. **Diffusers decoder interface** using `AutoencoderKLFlux2`.
 2. **Rift1Decoder metadata** in `config.json` for clear model identity.
-3. **32 latent channels** for compatibility with FLUX.2-style latent spaces.
+3. **32 latent channels** for compatible image latent spaces.
 4. **512px reconstruction training** with edge and frequency losses for sharper detail retention.
 5. **Single-file artifacts included** for decoder-focused workflows:
    - `diffusion_pytorch_model.safetensors`
@@ -37,11 +36,7 @@ The exported Diffusers runtime class remains `AutoencoderKLFlux2` for loader com
 
 Compatible target pipeline family:
 
-- FLUX.2-style Diffusers pipelines using `AutoencoderKLFlux2`
-- [FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B)
-- [FLUX.2-klein-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B)
-- [FLUX.2-klein-9b-kv](https://huggingface.co/black-forest-labs/FLUX.2-klein-9b-kv)
-- [FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev)
+- Diffusers image pipelines using `AutoencoderKLFlux2`
 
 # **Comparison**
 
@@ -69,33 +64,21 @@ vae = AutoencoderKLFlux2.from_pretrained(
 )
 ```
 
-If using a compatible FLUX.2 pipeline, pass this VAE when loading the pipeline:
+If using a compatible image pipeline, pass this VAE when loading the pipeline:
 
 ```python
 import torch
-from diffusers import Flux2KleinPipeline, AutoencoderKLFlux2
+from diffusers import AutoencoderKLFlux2
 
 device = "cuda"
 dtype = torch.bfloat16
 
-vae = AutoencoderKLFlux2.from_pretrained("Rift-ai/Rift.1-decoder", torch_dtype=dtype)
-pipe = Flux2KleinPipeline.from_pretrained(
-    "black-forest-labs/FLUX.2-klein-4B",
-    vae=vae,
+vae = AutoencoderKLFlux2.from_pretrained(
+    "Rift-ai/Rift.1-decoder",
     torch_dtype=dtype,
-)
-pipe.enable_model_cpu_offload()
-
-prompt = "A black cat holding a sign that says 'hello world' in typewriter font"
-image = pipe(
-    prompt=prompt,
-    height=1024,
-    width=1024,
-    guidance_scale=1.0,
-    num_inference_steps=4,
-    generator=torch.Generator(device=device).manual_seed(0),
-).images[0]
-image.save("rift-decoder-output.png")
+).to(device)
+
+# Pass `vae=vae` into a compatible Diffusers image pipeline.
 ```
 
 ---