Update README.md

README.md

@@ -21,7 +21,34 @@ import torch
 pipe = KandinskyV3PipelineIpAdapter.from_pretrained('ai-forever/kandinsky3_ip_adapter', torch_dtype=torch.float16, low_cpu_mem_usage=False, device_map=None)
 pipe = pipe.to('cuda')
 img = Image.open('path_to_img.jpg')
-out_img = pipe(caption, img=[img], weights=[1], negative_prompt='', height=1024, width=1024, guidance_scale=7.5, num_inference_steps=50, cut_context=1)[0][0]
+out_img = pipe('4k caption', img=[img], weights=[1], negative_prompt='', height=1024, width=1024, guidance_scale=7.5, num_inference_steps=50, cut_context=1)[0][0]
+```
+
+### Image + Image mixing
+
+```python
+from diffusers.models.attention_processor import Kandi3AttnProcessorIpAdapter, Kandi3AttnProcessor
+from diffusers.pipelines.kandinsky3.kandinsky3_pipeline_ip_adapter import KandinskyV3PipelineIpAdapter
+from PIL import Image
+import torch
+pipe = KandinskyV3PipelineIpAdapter.from_pretrained('ai-forever/kandinsky3_ip_adapter', torch_dtype=torch.float16, low_cpu_mem_usage=False, device_map=None)
+pipe = pipe.to('cuda')
+img1 = Image.open('path_to_img1.jpg')
+img2 = Image.open('path_to_img2.jpg')
 
+out_img = pipe('4k photo', img=[img1, img2], weights=[0.5, 0.5], negative_prompt='', height=1024, width=1024, guidance_scale=7.5, num_inference_steps=50, cut_context=1)[0][0]
+```
+
+### Text + Image mixing
 
+```python
+from diffusers.models.attention_processor import Kandi3AttnProcessorIpAdapter, Kandi3AttnProcessor
+from diffusers.pipelines.kandinsky3.kandinsky3_pipeline_ip_adapter import KandinskyV3PipelineIpAdapter
+from PIL import Image
+import torch
+pipe = KandinskyV3PipelineIpAdapter.from_pretrained('ai-forever/kandinsky3_ip_adapter', torch_dtype=torch.float16, low_cpu_mem_usage=False, device_map=None)
+pipe = pipe.to('cuda')
+img = Image.open('path_to_img.jpg')
+caption = 'cat, 4k photo'
+out_img = pipe(caption, img=[img], weights=[1], negative_prompt='', height=1024, width=1024, guidance_scale=7.5, num_inference_steps=50, cut_context=1, img_weight=0.5)[0][0]
 ```