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The zip file contains installers for Windows, RunPod, Massed Compute and a free Kaggle account notebook
The zip file contains installers for Windows, RunPod, Massed Compute and a free Kaggle account notebook
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It generates a VENV and install everything inside it. Works with Python 3.10.x - I suggest 3.10.11
It generates a VENV and install everything inside it. Works with Python 3.10.x - I suggest 3.10.11
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Also you need C++ tools and Git. You can follow this tutorial to install all : 
Also you need C++ tools and Git. You can follow this tutorial to install all : 
link
https://youtu.be/-NjNy7afOQ0
https://youtu.be/-NjNy7afOQ0
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Updated 27 May 2024 : 
Updated 27 May 2024 : 
link
https://www.patreon.com/posts/95759342
https://www.patreon.com/posts/95759342
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21 January 2024 Update
21 January 2024 Update
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SDXL model upgraded to ip-adapter-faceid-plusv2_sd15
SDXL model upgraded to ip-adapter-faceid-plusv2_sd15
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Kaggle Notebook upgraded to V3 and supports SDXL now
Kaggle Notebook upgraded to V3 and supports SDXL now
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First of all I want to thank you so much for this amazing model.
First of all I want to thank you so much for this amazing model.
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I have spent over 1 week to code the Gradio and prepare the video. I hope you let this thread remain and even add to the Readme file.
I have spent over 1 week to code the Gradio and prepare the video. I hope you let this thread remain and even add to the Readme file.
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After video has been published I even added face embedding caching mechanism. So now it will calculate face embedding vector only 1 time for each image, thus super speed up the image generation.
After video has been published I even added face embedding caching mechanism. So now it will calculate face embedding vector only 1 time for each image, thus super speed up the image generation.
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Instantly Transfer Face By Using IP-Adapter-FaceID: Full Tutorial & GUI For Windows, RunPod & Kaggle : 
Instantly Transfer Face By Using IP-Adapter-FaceID: Full Tutorial & GUI For Windows, RunPod & Kaggle : 
link
https://youtu.be/rjXsJ24kQQg
https://youtu.be/rjXsJ24kQQg
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chapters are like below
chapters are like below
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0:00 Introduction to IP-Adapter-FaceID full tutorial
0:00 Introduction to IP-Adapter-FaceID full tutorial
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2:19 Requirements to use IP-Adapter-FaceID gradio Web APP
2:19 Requirements to use IP-Adapter-FaceID gradio Web APP
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2:45 Where the Hugging Face models are downloaded by default on Windows
2:45 Where the Hugging Face models are downloaded by default on Windows
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3:12 How to change folder path where the Hugging Face models are downloaded and cached
3:12 How to change folder path where the Hugging Face models are downloaded and cached
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3:39 How to install IP-Adapter-FaceID Gradio Web APP and use on Windows
3:39 How to install IP-Adapter-FaceID Gradio Web APP and use on Windows
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5:35 How to start the IP-Adapter-FaceID Web UI after the installation
5:35 How to start the IP-Adapter-FaceID Web UI after the installation
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5:46 How to use Stable Diffusion XL (SDXL) models with IP-Adapter-FaceID
5:46 How to use Stable Diffusion XL (SDXL) models with IP-Adapter-FaceID
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5:56 How to select your input face and start generating 0-shot face transferred new amazing images
5:56 How to select your input face and start generating 0-shot face transferred new amazing images
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6:06 What does each option on the Web UI do explanations
6:06 What does each option on the Web UI do explanations
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The zip file contains installers for Windows, RunPod, Massed Compute and a free Kaggle account notebook

It generates a VENV and install everything inside it. Works with Python 3.10.x - I suggest 3.10.11

Also you need C++ tools and Git. You can follow this tutorial to install all : https://youtu.be/-NjNy7afOQ0

Updated 27 May 2024 : https://www.patreon.com/posts/95759342

21 January 2024 Update
SDXL model upgraded to ip-adapter-faceid-plusv2_sd15
Kaggle Notebook upgraded to V3 and supports SDXL now

First of all I want to thank you so much for this amazing model.

I have spent over 1 week to code the Gradio and prepare the video. I hope you let this thread remain and even add to the Readme file.

After video has been published I even added face embedding caching mechanism. So now it will calculate face embedding vector only 1 time for each image, thus super speed up the image generation.

Instantly Transfer Face By Using IP-Adapter-FaceID: Full Tutorial & GUI For Windows, RunPod & Kaggle : https://youtu.be/rjXsJ24kQQg

chapters are like below

0:00 Introduction to IP-Adapter-FaceID full tutorial
2:19 Requirements to use IP-Adapter-FaceID gradio Web APP
2:45 Where the Hugging Face models are downloaded by default on Windows
3:12 How to change folder path where the Hugging Face models are downloaded and cached
3:39 How to install IP-Adapter-FaceID Gradio Web APP and use on Windows
5:35 How to start the IP-Adapter-FaceID Web UI after the installation
5:46 How to use Stable Diffusion XL (SDXL) models with IP-Adapter-FaceID
5:56 How to select your input face and start generating 0-shot face transferred new amazing images
6:06 What does each option on the Web UI do explanations


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