Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+base_model: runwayml/stable-diffusion-v1-5
+tags:
+- stable-diffusion
+- diffusers
+- lora
+- scientific-machine-learning
+- physics-simulation
+- visual-reasoning
+---
+
+# VR-LoRA: N-Body Physics Simulator (SD-v1.5)
+
+This repository contains a Visual Reasoning LoRA (VR-LoRA) fine-tuned on `runwayml/stable-diffusion-v1-5` to predict the temporal evolution of a 3-body gravitational system.
+
+This model is the primary output of the paper: **"Visual Reasoning Transfer: Leveraging Pretrained Visual Models for Physical and Temporal Prediction"** (link to paper coming soon).
+
+## Model Description
+
+The model does not generate images. Instead, it acts as a dynamics engine in latent space. When given a latent representation of a physical state (encoded as a "spatial field image"), it predicts the latent representation of the next physical state.
+
+This LoRA (final) was trained for 15,000 steps on a synthetic dataset of 10,000 N-body trajectories.
+
+*   **Research Project Repository:** [https://github.com/sandner-art/SC-Visual-Reasoning](https://github.com/sandner-art/SC-Visual-Reasoning)
+*   **Training Dataset:** [huggingface.co/datasets/sandner/n-body-trajectories-for-vrlora](https://huggingface.co/datasets/YourUsername/n-body-trajectories-for-vrlora) (Replace with your link)
+
+## How to Use
+
+This LoRA is designed to be used with the evaluation script found in the main research repository. It is not intended for standard text-to-image generation.
+
+```python
+# See the evaluate_vr_lora.py script in the main GitHub repo for a full example.
+from diffusers import StableDiffusionPipeline
+
+base_model = "runwayml/stable-diffusion-v1-5"
+lora_model = "YourUsername/vr-lora-physics-sd15" # Replace with your repo name
+
+pipeline = StableDiffusionPipeline.from_pretrained(base_model)
+pipeline.load_lora_weights(lora_model)
+pipeline.to("cuda")
+
+# Now the `pipeline.unet` component is ready for physics simulation.
+unet = pipeline.unet
+# ...