upload

.gitattributes

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+transform2venom.safetensors filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+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: >-
+    "The video begins with a anime young character with long hair. 5en3m venom transformation. Transform into a venom character transformation. Venom is depicted with his iconic black symbiote body, large white eyes with black pupils, sharp teeth, and a menacing expression. The transformation is smooth and seamless, blending the human figure with the monstrous ."
+  output:
+    url: example_videos/9_epoch40.mp4
+- text: >-
+    The video begins with a woman wearing black clothes. 5en3m venom transformation. Transform into a venom character transformation. Venom is depicted with his iconic black symbiote body, large white eyes with black pupils, sharp teeth, and a menacing expression. The transformation is smooth and seamless, blending the human figure with the monstrous .
+  output:
+    url: example_videos/8_epoch40.mp4
+- text: >-
+    The video begins with a man wearing a suit. 5en3m venom transformation. Transform into a venom character transformation. Venom is depicted with his iconic black symbiote body, large white eyes with black pupils, sharp teeth, and a menacing expression.The transformation is smooth and seamless, blending the human figure with the monstrous .
+  output:
+    url: example_videos/10_epoch40.mp4
+---
+
+<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
+  <h1 style="color: #24292e; margin-top: 0;">Transform to Venom Effect LoRA for Wan2.1 14B I2V 480p</h1>
+  
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Overview</h2>
+    <p>This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to transform any object to venom in an image. The effect works on a wide variety of objects, from animals to vehicles to people!</p>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Features</h2>
+    <ul style="margin-bottom: 0;">
+      <li>Transform any image into a video of it being squished</li>
+      <li>Trained on the Wan2.1 14B 480p I2V base model</li>
+      <li>Consistent results across different object types</li>
+      <li>Simple prompt structure that's easy to adapt</li>
+    </ul>
+  </div>
+
+</div>
+
+<Gallery />
+
+# Model File and Inference Workflow
+
+## 📥 Download Links:
+
+- [transform2venom.safetensors](./transform2venom.safetensors) - LoRA Model File
+- [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)
+
+# Note: Choose Unipcm scheduler to generate higher quality videos for Wan
+flow_shift = 3.0  # 5.0 for 720P, 3.0 for 480P
+scheduler = UniPCMultistepScheduler(
+    prediction_type="flow_prediction",
+    use_flow_sigmas=True,
+    num_train_timesteps=1000,
+    flow_shift=flow_shift,
+    scheduler=scheduler,
+)
+pipe = WanImageToVideoPipeline.from_pretrained(model_id, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+pipe.load_lora_weights("passenger12138/Transform2Venom")
+
+pipe.enable_model_cpu_offload() #for low-vram environments
+
+prompt = "The video begins with a man wearing a suit. 5en3m venom transformation. Transform into a venom character transformation. Venom is depicted with his iconic black symbiote body, large white eyes with black pupils, sharp teeth, and a menacing expression. The transformation is smooth and seamless, blending the human figure with the monstrous ."
+
+image = load_image('./test_i2vlora_imgs/1.png')
+
+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;">
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Recommended Settings</h2>
+    <ul style="margin-bottom: 0;">
+      <li><b>LoRA Strength:</b> 1.0</li>
+      <li><b>Embedded Guidance Scale:</b> 6.0</li>
+      <li><b>Flow Shift:</b> 3.0</li>
+    </ul>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2>
+    <p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">5en3m venom transformation.</code></p>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Prompt Template</h2>
+    <p>For best results, use this prompt structure:</p>
+    <div style="background-color: #f0f0f0; padding: 12px; border-radius: 6px; margin: 10px 0;">
+      <i>The video begins with a [object]. 5en3m venom transformation. Transform into a venom character transformation. Venom is depicted with his iconic black symbiote body, large white eyes with black pupils, sharp teeth, and a menacing expression. The transformation is smooth and seamless, blending the human figure with the monstrous .</i>
+    </div>
+    <p>Simply replace <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">[object]</code> with whatever you want to see transform to venom!</p>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">ComfyUI Workflow</h2>
+    <p>This LoRA works with a modified version of <a href="https://github.com/kijai/ComfyUI-WanVideoWrapper/blob/main/example_workflows/wanvideo_480p_I2V_example_02.json" style="color: #0366d6; text-decoration: none;">Kijai's Wan Video Wrapper workflow</a>. The main modification is adding a Wan LoRA node connected to the base model.</p>
+
+  </div>
+</div>
+
+<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Model Information</h2>
+    <p>The model weights are available in Safetensors format. See the Downloads section above.</p>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Training Details</h2>
+    <ul style="margin-bottom: 0;">
+      <li><b>Base Model:</b> Wan2.1 14B I2V 480p</li>
+      <li><b>Training Data:</b> 1.5 minutes of video (40 short clips of things being squished)</li>
+      <li><b>Epochs:</b> 40</li>
+    </ul>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Additional Information</h2>
+    <p>Training was done using <a href="https://github.com/tdrussell/diffusion-pipe" style="color: #0366d6; text-decoration: none;">Diffusion Pipe for Training</a></p>
+  </div>
+
+  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+    <h2 style="color: #24292e; margin-top: 0;">Acknowledgments</h2>
+    <p style="margin-bottom: 0;">Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts and RemadeAI some case!</p>
+  </div>
+</div>

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+        "fp8_e4m3fn",
+        "offload_device",
+        "sageattn"
+      ]
+    },
+    {
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+      "type": "WanVideoLoraSelect",
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+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "prev_lora",
+          "type": "WANVIDLORA",
+          "shape": 7,
+          "link": null
+        },
+        {
+          "name": "blocks",
+          "type": "SELECTEDBLOCKS",
+          "shape": 7,
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "lora",
+          "type": "WANVIDLORA",
+          "links": [
+            41
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "WanVideoLoraSelect"
+      },
+      "widgets_values": [
+        "Squish\\squish_18.safetensors",
+        1
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+    },
+    {
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+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "sdpa should work too, haven't tested flaash\n\nfp8_fast seems to cause huge quality degradation"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 32,
+      "type": "WanVideoBlockSwap",
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+      "outputs": [
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+          "links": [
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+          "slot_index": 0
+        }
+      ],
+      "properties": {
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+      },
+      "widgets_values": [
+        10
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+    },
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+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Models:\nhttps://huggingface.co/Kijai/WanVideo_comfy/tree/main"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 16,
+      "type": "WanVideoTextEncode",
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+      "inputs": [
+        {
+          "name": "t5",
+          "type": "WANTEXTENCODER",
+          "link": 15
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text_embeds",
+          "type": "WANVIDEOTEXTEMBEDS",
+          "links": [
+            30
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "WanVideoTextEncode"
+      },
+      "widgets_values": [
+        "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.",
+        "bad quality video",
+        true,
+        [
+          false,
+          true
+        ],
+        [
+          false,
+          true
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+      1,
+      "LATENT"
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+      0,
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+      "WANVIDLORA"
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+  ],
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+  "config": {},
+  "extra": {
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+      "offset": {
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+    "node_versions": {
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+      "ComfyUI-VideoHelperSuite": "565208bfe0a8050193ae3c8e61c96b6200dd9506",
+      "comfy-core": "0.3.18"
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+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true,
+    "ue_links": [],
+    "workspace_info": {
+      "id": "mZ-DLut47Mni3MFPHoL4Y",
+      "saveLock": false,
+      "cloudID": null,
+      "coverMediaPath": null
+    }
+  },
+  "version": 0.4
+}