Update README.md

README.md

@@ -36,49 +36,12 @@ We release our two models:
 
 Weights of the model are loaded internally but if want to change them one can use the following example:
 
-```python 
-from huggingface_hub import hf_hub_download
-from kandinsky3 import get_T2I_unet, get_T5encoder, get_movq, Kandinsky3T2IPipeline
-
-unet_path = hf_hub_download(
-        repo_id="ai-forever/Kandinsky3.0", filename='weights/kandinsky3.pt')
-)
-
-movq_path = hf_hub_download(
-          repo_id="ai-forever/Kandinsky3.0", filename='weights/movq.pt')
-)
-unet, null_embedding, projections_state_dict = get_T2I_unet(device, unet_path, fp16=fp16)
-processor, condition_encoders = get_T5encoder(device, text_encode_path, projections_state_dict, fp16=fp16)
-movq = get_movq(device, movq_path, fp16=fp16)
-t2i_pipe =  Kandinsky3T2IPipeline(device, unet, null_embedding, processor, condition_encoders, movq, fp16=fp16)
-```
-
-```python 
-from huggingface_hub import hf_hub_download
-from kandinsky3 import get_inpainting_unet, get_T5encoder, get_movq, Kandinsky3InpaintingPipeline
-
-inpainting_unet_path = hf_hub_download(
-          repo_id="ai-forever/Kandinsky3.0", filename='weights/kandinsky3_inpainting.pt', cache_dir=cache_dir
-)
-movq_path = hf_hub_download(
-          repo_id="ai-forever/Kandinsky3.0", filename='weights/movq.pt')
-)
-
-unet, null_embedding, projections_state_dict = get_inpainting_unet(device, unet_path, fp16=fp16)
-processor, condition_encoders = get_T5encoder(device, text_encode_path, projections_state_dict, fp16=fp16)
-movq = get_movq(device, movq_path, fp16=False) #MoVQ ooesn't work properly in fp16 on inpainting
-pipe = Kandinsky3InpaintingPipeline(device, unet, null_embedding, processor, condition_encoders, movq, fp16=fp16)
-```
-
 ## Installing
 
 To install repo first one need to create conda environment:
 
 ```
-conda create -n kandinsky -y python=3.8;
-source activate kandinsky;
-pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 torchaudio==0.10.1 -f https://download.pytorch.org/whl/cu113/torch_stable.html;
-pip install -r requirements.txt;
+pip install git+https://github.com/ai-forever/diffusers_kandinsky3.git
 ```
 The exact dependencies is got using `pip freeze` and can be found in `exact_requirements.txt`
 
@@ -89,23 +52,13 @@ Check our jupyter notebooks with examples in `./examples` folder
 ### 1. text2image
 
 ```python
-from kandinsky3 import get_T2I_pipeline
-
-t2i_pipe = get_T2I_pipeline('cuda', fp16=True)
-
-image = t2i_pipe( "A cute corgi lives in a house made out of sushi.")
-```
-
-### 2. inpainting
-
-```python
-from kandinsky3 import get_inpainting_pipeline
+from diffusers import KandinskyV3Pipeline
+import torch
 
-inp_pipe = get_inpainting_pipeline('cuda', fp16=True)
+pipe = KandinskyV3Img2ImgPipeline.from_pretrained('kandinsky-community/kandinsky-3', torch_dtype=torch.float16)
+pipe = pipe.to('cuda')
 
-image = ... # PIL Image
-mask = ... # Numpy array (HxW). Set 1 where image should be masked
-image = inp_pipe( "A cute corgi lives in a house made out of sushi.", image, mask)
+image = pipe("A cute corgi lives in a house made out of sushi.")
 ```
 
 ## Examples of generations