Update README.md

README.md

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----
-license: mit
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+# galaxy_gen
+
+`galaxy_gen` is a library to generate galaxy data/distributions. The models used are present in this page.
+
+## Installation
+
+You can install the package using pip:
+
+```sh
+pip install galaxy_gen
+```
+
+## Usage
+Here is an example of how to use the galaxy_gen library:
+
+```python
+# example_usage.py
+import torch
+import matplotlib.pyplot as plt
+import galaxy_gen
+from galaxy_gen.sampler import load_model, generate_samples
+import os
+
+# Path to your saved model checkpoint.
+model_path = os.path.join(os.path.dirname(galaxy_gen.__file__), 'models/sample_model')
+device = 'cpu'  # or 'cuda' if you have a GPU
+
+# Load the model.
+model = load_sample_model(model_path, device=device)
+
+# Generate random samples.
+samples = generate_samples(model)
+
+# (Optional) Visualize the samples.
+samples = samples.cpu().numpy()
+fig, axes = plt.subplots(4, 4, figsize=(8, 8))
+for i, ax in enumerate(axes.flatten()):
+    ax.imshow(samples[i][0], cmap='gray')
+    ax.axis('off')
+plt.show()
+```
+
+Another expample to use the pre-trained model
+```python
+# example_usage.py
+import torch
+import matplotlib.pyplot as plt
+from galaxy_gen.sampler import load_model, generate_metallicity_samples, generate_formationtime_samples
+
+# Path to your saved model checkpoint.
+model_path = 'models/formationtime_model.pth'
+device = 'cpu'  # or 'cuda' if you have a GPU
+
+# Load the model.
+model = load_model("formation_time",model_path, device=device)
+
+# Generate random samples.
+samples = generate_formationtime_samples(model)
+
+# (Optional) Visualize the samples.
+samples = samples.cpu().numpy()
+fig, axes = plt.subplots(4, 4, figsize=(8, 8))
+for i, ax in enumerate(axes.flatten()):
+    ax.imshow(samples[i][0])
+    ax.axis('off')
+plt.show()
+
+```
+
+## License
+This project is licensed under the MIT License - see the LICENSE file for details.