Update README.md

README.md

@@ -12,42 +12,37 @@ tags:
 - characterization
 ---
 
-# Model Card for Model ID
+# UniEM-Gen
 
 <!-- Provide a quick summary of what the model is/does. -->
 
+## 📘 Model Summary  
+This is the text-to-image diffusion model trained on the complete **[UniEM-3M](https://huggingface.co/datasets/NNNan/UniEM-3M)** dataset.  
+It is designed for **electron microscopy (EM)-style image generation**, enabling:  
+- Scientific data augmentation  
+- Proxy generation for microstructural distributions  
+- Multimodal research in materials science
 
+---
 
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+## 🚀 Usage Example  
 
-## Uses
+### Using `diffusers`
+```python
+from diffusers import StableDiffusionPipeline
+import torch
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+# Load model from Hugging Face
+model_id = "NNNan/UniEM-Gen"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
 
-### Direct Use
+# Example prompt
+prompt = "High-resolution electron micrograph of nanoparticles with spherical morphology, high contrast"
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+# Generate image
+image = pipe(prompt).images[0]
 
-[More Information Needed]
+# Save or display
+image.save("generated_em.png")
+image.show()