Update README.md

README.md

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+# AstroPT Euclid VIS Model
 
-# Euclid astroPT: a Foundation Model for Astronomy
+Pre-trained AstroPT model for single-band analysis using Euclid VIS imaging.
 
-Here we have the model files for the astroPT project trained on Euclid VIS images, the code to run inference
-with these models is found here:
-[https://github.com/smith42/astropt](https://github.com/smith42/astropt)
+## Overview
 
+This is a pre-trained checkpoint for the **AstroPT** framework, trained on Euclid VIS band imaging from the Euclid Q1 dataset. 
 
+**Citation**: Euclid Collaboration: Siudek, M et al. 2025 ([arXiv:2503.15312](https://ui.adsabs.harvard.edu/abs/2025arXiv250315312E/abstract))
+
+## Quick Start
+
+### Load Model
+
+```python
+import torch
+from pathlib import Path
+
+# Load model checkpoint
+model_path = "astropt/090M/ckpt.pt"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Load state dict
+checkpoint = torch.load(model_path, map_location=device)
+# Initialize your model architecture here
+# model.load_state_dict(checkpoint)
+```
+
+### Inference
+
+```python
+from datasets import load_dataset
+import torch
+
+# Load dataset
+dataset = load_dataset(
+    "msiudek/astroPT_euclid_dataset",
+    split="train_batch_1",
+    streaming=True
+)
+
+# Run inference
+model.eval()
+with torch.no_grad():
+    for sample in dataset:
+        vis_image = sample['VIS_image']  # 224×224
+        vis_image = torch.tensor(vis_image, dtype=torch.float32)
+        vis_image = vis_image.unsqueeze(0).unsqueeze(0)  # [1, 1, 224, 224]
+        
+        # Get embeddings
+        embeddings = model(vis_image)
+```
+
+## Training Data
+
+- **Dataset**: [AstroPT Euclid Dataset](https://huggingface.co/datasets/msiudek/astroPT_euclid_dataset)
+- **VIS Band**: Euclid VIS (0.55–0.90 μm)
+
+## Related Models
+
+- [AstroPT VIS+NISP Model](https://huggingface.co/msiudek/astroPT_euclid_VIS_NISP_model): Multi-band (VIS + NISP)
+- [AstroPT VIS+NISP+SED Model](https://huggingface.co/msiudek/astroPT_euclid_VIS_NISP_SED_model): Multi-modal (imaging + photometry)
+
+## Datasets
+
+- **Imaging**: [astroPT_euclid_dataset](https://huggingface.co/datasets/msiudek/astroPT_euclid_dataset)
+- **Metadata**: [astroPT_euclid_metadata](https://huggingface.co/datasets/msiudek/astroPT_euclid_metadata)
+
+## Code & Documentation
+
+For inference code, training scripts, and tutorials, visit the **[AstroPT GitHub Repository](https://github.com/Smith42/astroPT)**.
+
+## Citation
+
+```bibtex
+@article{Siudek2025,
+  title={AstroPT: Astronomical Physics Transformers for Multi-modal Learning},
+  author={Siudek, M and others},
+  journal={Euclid Collaboration},
+  eprint={2503.15312},
+  archivePrefix={arXiv},
+  year={2025},
+  url={https://ui.adsabs.harvard.edu/abs/2025arXiv250315312E/abstract}
+}
+```
+
+## License
+
+CC-BY-4.0
+
+---
+
+**Last Updated**: December 2025  
+**Model Version**: 1.0