Update README.md

README.md

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 # LibreFLUX-IP-Adapter
 ![Example: Control image vs result](examples/matrix_edge.png)
 
-This model/pipeline is the product of my [LibreFlux IP-Adapter training repo](https://github.com/NeuralVFX/LibreFLUX-IP-Adapter), which uses  [LibreFLUX](https://huggingface.co/jimmycarter/LibreFLUX) as the underlying Transformer model. The Adapter design is roughly based on InstantX's IP Adapter
+This model/pipeline is the product of my [LibreFlux IP-Adapter training repo](https://github.com/NeuralVFX/LibreFLUX-IP-Adapter), which uses  [LibreFLUX](https://huggingface.co/jimmycarter/LibreFLUX) as the underlying Transformer model. The IP Adapter and Attention Wrapper design is roughly based on the [InstantX IP Adapter](https://huggingface.co/InstantX/FLUX.1-dev-IP-Adapter/)
 
 I used transfer learning, to fintune the InstantX weights until they worked with LibreFlux and attention masking. For the dataset, I trained on laion2b-squareish-1024px for 20,000 iterations.
 
@@ -25,8 +25,8 @@ I used transfer learning, to fintune the InstantX weights until they worked with
 - Trained in same non-distilled fashion 
 - Uses Attention Masking
 - Uses CFG during Inference
-
 # Fun Facts
+- Fine tuned from these weights: [https://huggingface.co/InstantX/FLUX.1-dev-IP-Adapter/](https://huggingface.co/InstantX/FLUX.1-dev-IP-Adapter/)
 - Trained on the [laion2b-squareish-1024px Dataset](https://huggingface.co/datasets/opendiffusionai/laion2b-squareish-1024px/)
 - Trained using this repo: [https://github.com/NeuralVFX/LibreFLUX-IP-Adapter](https://github.com/NeuralVFX/LibreFLUX-IP-Adapter)
 - Transformer model used: [https://huggingface.co/jimmycarter/LibreFlux](https://huggingface.co/jimmycarter/LibreFlux)