Update README.md

README.md

@@ -1,3 +1,60 @@
 ---
 license: mit
 ---
+
+### Simple running code is based on [CoLLaVO-Github](https://github.com/ByungKwanLee/CoLLaVO).
+
+You need only the following seven steps.
+
+### [0] Download Github Code of CoLLaVO, install the required libraries, set the necessary environment variable (README.md explains in detail! Don't Worry!).
+
+```bash
+git clone https://github.com/ByungKwanLee/CoLLaVO
+bash install
+```
+
+### [1] Loading Image
+
+```python
+from PIL import Image
+from torchvision.transforms import Resize
+from torchvision.transforms.functional import pil_to_tensor
+image_path = "figures/crayon_image.jpg"
+image = Resize(size=(490, 490), antialias=False)(pil_to_tensor(Image.open(image_path)))
+```
+
+### [2] Instruction Prompt
+
+```python
+prompt = "Describe this image in detail."
+```
+
+### [3] Loading CoLlaVO
+```python
+from collavo.load_collavo import prepare_collavo
+collavo_model, collavo_processor, seg_model, seg_processor = prepare_collavo(collavo_path='BK-Lee/CoLLaVO-7B', bits=4, dtype='fp16')
+
+```
+
+### [4] Pre-processing for CoLLaVO
+```python
+collavo_inputs = collavo_model.demo_process(image=image, 
+                                    prompt=prompt, 
+                                    processor=collavo_processor,
+                                    seg_model=seg_model,
+                                    seg_processor=seg_processor,
+                                    device='cuda:0')
+```
+
+### [5] Generate
+```python
+import torch
+with torch.inference_mode():
+    generate_ids = collavo_model.generate(**collavo_inputs, do_sample=True, temperature=0.9, top_p=0.95, max_new_tokens=256, use_cache=True)
+```
+
+### [6] Decoding
+```python
+answer = collavo_processor.batch_decode(generate_ids, skip_special_tokens=True)[0].split('[U')[0]
+print(answer)
+```