Fix tags and add diffusers inference example

README.md

@@ -4,7 +4,34 @@ language:
 - en
 base_model:
 - Wan-AI/Wan2.1-I2V-14B-480P
+- Wan-AI/Wan2.1-I2V-14B-480P-Diffusers
 pipeline_tag: image-to-video
+tags:
+- text-to-image
+- lora
+- diffusers
+- template:diffusion-lora
+widget:
+  - text: >-
+      In the video, a miniature dog is presented. The dog is held in a person's hands. The person then presses on the dog, causing a sq41sh squish effect. The person keeps pressing down on the dog, further showing the sq41sh squish effect.
+    output:
+      url: example_videos/dog_squish.mp4
+  - text: >-
+      In the video, a miniature tank is presented. The tank is held in a person's hands. The person then presses on the tank, causing a sq41sh squish effect. The person keeps pressing down on the tank, further showing the sq41sh squish effect.
+    output:
+      url: example_videos/tank_squish.mp4
+  - text: >-
+      In the video, a miniature balloon is presented. The balloon is held in a person's hands. The person then presses on the balloon, causing a sq41sh squish effect. The person keeps pressing down on the balloon, further showing the sq41sh squish effect.
+    output:
+      url: example_videos/balloon_squish.mp4
+  - text: >-
+      In the video, a miniature rodent is presented. The rodent is held in a person's hands. The person then presses on the rodent, causing a sq41sh squish effect. The person keeps pressing down on the rodent, further showing the sq41sh squish effect.
+    output:
+      url: example_videos/rodent_squish.mp4
+  - text: >-
+      In the video, a miniature person is presented. The person is held in a person's hands. The person then presses on the person, causing a sq41sh squish effect. The person keeps pressing down on the person, further showing the sq41sh squish effect.
+    output:
+      url: example_videos/person_squish.mp4
 ---
 <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
   <h1 style="color: #24292e; margin-top: 0;">Squish Effect LoRA for Wan2.1 14B I2V 480p</h1>
@@ -33,6 +60,8 @@ pipeline_tag: image-to-video
   </div>
 </div>
 
+<Gallery />
+
 ## Examples
 
 ### Clay Dog
@@ -79,7 +108,52 @@ pipeline_tag: image-to-video
 ## 📥 Download Links:
 
 - [squish_18.safetensors](./squish_18.safetensors) - LoRA Model File
-- [wan_img2video_lora_workflow.json](./workflow/wan_img2video_lora_workflow.json) - Wan I2V with LoRA Workflow
+- [wan_img2video_lora_workflow.json](./workflow/wan_img2video_lora_workflow.json) - Wan I2V with LoRA Workflow for ComfyUI
+
+## Using with Diffusers
+```py
+pip install git+https://github.com/huggingface/diffusers.git
+```
+
+```py
+import torch
+from diffusers.utils import export_to_video, load_image
+from diffusers import AutoencoderKLWan, WanImageToVideoPipeline
+from transformers import CLIPVisionModel
+import numpy as np
+
+model_id = "Wan-AI/Wan2.1-I2V-14B-480P-Diffusers"
+image_encoder = CLIPVisionModel.from_pretrained(model_id, subfolder="image_encoder", torch_dtype=torch.float32)
+vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
+pipe = WanImageToVideoPipeline.from_pretrained(model_id, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+pipe.load_lora_weights("Remade/Squish")
+
+pipe.enable_model_cpu_offload() #for low-vram environments
+
+prompt = "In the video, a miniature cat toy is presented. The cat toy is held in a person's hands. The person then presses on the cat toy, causing a sq41sh squish effect. The person keeps pressing down on the cat toy, further showing the sq41sh squish effect."
+
+image = load_image("https://huggingface.co/datasets/diffusers/cat_toy_example/resolve/main/1.jpeg")
+
+max_area = 480 * 832
+aspect_ratio = image.height / image.width
+mod_value = pipe.vae_scale_factor_spatial * pipe.transformer.config.patch_size[1]
+height = round(np.sqrt(max_area * aspect_ratio)) // mod_value * mod_value
+width = round(np.sqrt(max_area / aspect_ratio)) // mod_value * mod_value
+image = image.resize((width, height))
+
+output = pipe(
+    image=image,
+    prompt=prompt,
+    height=height,
+    width=width,
+    num_frames=81,
+    guidance_scale=5.0,
+    num_inference_steps=28
+).frames[0]
+export_to_video(output, "output.mp4", fps=16)
+```
 
 ---
 <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">