Update README.md

README.md

@@ -28,6 +28,43 @@ With a pipeline of expert models, we can infer spatial relationships between obj
 - **Developed by:** remyx.ai
 - **Model type:** MultiModal Model, Vision Language Model, Llama 3
 
+## Quick Start
+
+To run SpaceMantis, follow these steps:
+
+```python
+import torch
+from PIL import Image
+from models.mllava import MLlavaProcessor, LlavaForConditionalGeneration, chat_mllava
+
+# Load the model and processor
+attn_implementation = None  # or "flash_attention_2"
+processor = MLlavaProcessor.from_pretrained("remyxai/SpaceMantis")
+model = LlavaForConditionalGeneration.from_pretrained("remyxai/SpaceMantis", device_map="cuda", torch_dtype=torch.float16, attn_implementation=attn_implementation)
+
+generation_kwargs = {
+    "max_new_tokens": 1024,
+    "num_beams": 1,
+    "do_sample": False
+}
+
+# Function to run inference
+def run_inference(image_path, content):
+    # Load the image
+    image = Image.open(image_path).convert("RGB")
+    # Convert the image to base64
+    images = [image]
+    # Run the inference
+    response, history = chat_mllava(content, images, model, processor, **generation_kwargs)
+    return response
+
+# Example usage
+image_path = "path/to/your/image.jpg"
+content = "Your question here."
+response = run_inference(image_path, content)
+print("Response:", response)
+```
+
 ### Model Sources
 - **Dataset:** [SpaceLLaVA](https://huggingface.co/datasets/remyxai/vqasynth_spacellava)
 - **Repository:** [VQASynth](https://github.com/remyxai/VQASynth/tree/main)