Update README.md

README.md

@@ -38,12 +38,12 @@ scheduler = LCMScheduler
 Lower guidance gives cleaner results.
 Higher guidance may introduce instability due to LCM behavior.
 
-🧠 Why LiteVision?
+# 🧠 Why LiteVision?
 Traditional SD 1.5 models require 20–30 steps for good quality. LiteVision ONLY requires about 6 steps.
 
 
 
-🛠 Usage
+# 🛠 Usage
 python
 ```
 Copy code
@@ -66,33 +66,21 @@ image = pipe(
 image.save("litevision_output.png")
 ```
 
-📦 Architecture
-UNet: SD 1.5 compatible
-
-VAE: AutoencoderKL
-
-Text Encoder: CLIP
-
-Scheduler: LCMScheduler (recommended)
-
-Safety Checker: StableDiffusionSafetyChecker
-
-🧪 Benchmark (LCM)
-Model	Steps	Time	Quality
-SD 1.5	20	Slow	High
-LiteVision-v1	6	Fast	High
-
-(Tested on RTX-class GPU)
-
-⚠ Notes
+# ⚠ Notes
 Designed specifically for LCM scheduler.
 
 Not tuned for traditional DDIM/PNDM high-step sampling.
 
 Use FP16 for optimal performance.
 
-👤 Author
+# 👤 Author
 HyHorX
 
-License
-Same as Stable Diffusion 1.5.
+# License
+This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:
+
+- You can't use the model to deliberately produce nor share illegal or harmful outputs or content
+  
+- The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
+  
+- You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license here