Update README.md

README.md

@@ -12,12 +12,13 @@ base_model: jimmycarter/LibreFLUX
 This model/pipeline is the product of my [LibreFlux ControlNet training repo](https://github.com/NeuralVFX/LibreFLUX-ControlNet). For the dataset I auto labeled 165K images from the SA1B dataset, and trained for that many iterations. I've tested using this ControlNet model as a base for transfer learning to less generic datasets, the results are good! 
 
 # Fun Facts
-- Uses Attention Masking
-- Inference runs with CFG
+- Trained in non-distilled fashion in style of: [https://huggingface.co/jimmycarter/LibreFLUX](https://huggingface.co/jimmycarter/LibreFLUX)
+- Uses Attention Masking (LibreFLUX style)
+- Inference runs with CFG (LibreFLUX style)
 - Trained on 165K segmented images from Meta's [SA1B Dataset](https://ai.meta.com/datasets/segment-anything/)
-- Trained using: [https://github.com/NeuralVFX/LibreFLUX-ControlNet](https://github.com/NeuralVFX/LibreFLUX-ControlNet)
-- Transformer model used: [https://huggingface.co/jimmycarter/LibreFLUX](https://huggingface.co/jimmycarter/LibreFLUX)
-- Inference code adapted from: [https://github.com/bghira/SimpleTuner](https://github.com/bghira/SimpleTuner)
+- Trained using this repo: [https://github.com/NeuralVFX/LibreFLUX-ControlNet](https://github.com/NeuralVFX/LibreFLUX-ControlNet)
+- Transformer model used: [https://huggingface.co/jimmycarter/LibreFlux-SimpleTuner](https://huggingface.co/jimmycarter/LibreFlux-SimpleTuner)
+- Inference code roughly adapted from: [https://github.com/bghira/SimpleTuner](https://github.com/bghira/SimpleTuner)
   
 # Compatibility
 ```py