Update README.md

README.md

@@ -1,35 +1,47 @@
 ---
 base_model: timbrooks/instruct-pix2pix
 library_name: diffusers
-license: creativeml-openrail-m
+license: apache-2.0
 tags:
 - stable-diffusion
 - stable-diffusion-diffusers
 - text-to-image
 - diffusers
 - diffusers-training
-- lora
 inference: true
+datasets:
+- SherryXTChen/InstructCLIP-InstructPix2Pix-Data
+language:
+- en
 ---
 
-<!-- This model card has been generated automatically according to the information the training script had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# InstructCLIP: Improving Instruction-Guided Image Editing with Automated Data Refinement Using Contrastive Learning
 
+GitHub: https://github.com/SherryXTChen/InstructCLIP.git
 
-
-
-## Intended uses & limitations
-
-#### How to use
+## Example
 
 ```python
-# TODO: add an example code snippet for running this diffusion pipeline
-```
-
-#### Limitations and bias
-
-[TODO: provide examples of latent issues and potential remediations]
-
-## Training details
-
-[TODO: describe the data used to train the model]
+import PIL
+import requests
+import torch
+from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
+
+model_id = "timbrooks/instruct-pix2pix"
+pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe.load_lora_weights("SherryXTChen/InstructCLIP-InstructPix2Pix")
+pipe.to("cuda")
+pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+
+url = "https://raw.githubusercontent.com/SherryXTChen/Instruct-CLIP/main/assets/1_input.jpg"
+def download_image(url):
+    image = PIL.Image.open(requests.get(url, stream=True).raw)
+    image = PIL.ImageOps.exif_transpose(image)
+    image = image.convert("RGB")
+    return image
+image = download_image(url)
+
+prompt = "as a 3 d sculpture"
+images = pipe(prompt, image=image, num_inference_steps=20).images
+images[0].save("output.jpg")
+```