Furkan Gözükara
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Tencent InstantCharacter 1-Click Installers for Windows, RunPod and Massed Compute, Supports RTX 5000 series as well
🕑 Added 2025-05-14 01:15:00 +0000 UTC1-Click to install Tencent InstantCharacter on Windows, RunPod and Massed Compute with more advanced Gradio App
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Latest installer zip file : InstantCharacter_v4.zip
Official repo : https://github.com/Tencent/InstantCharacter
I have significantly improved the official Repo app
Put FLUX LoRAs into loras folder, it will download 3 LoRAs by default
It will download necessary models into models folder automatically
Lower Character Scale makes it more stylized like 0.6, 0.8 etc
Also official repo Gradio was completely broken, fixed, improved, added new features like automatically save every generated image, number of generations and more
4 September 2025 Update
Bugs fixed and tested and working
Please extract latest zip file, delete your venv folder and run Windows_Install_Update.bat
Windows Requirements
Python 3.10.11, FFmpeg, CUDA 12.8 or above, cuDNN 9.4 or above, C++ tools, MSVC and Git
If it doesn't work make sure to below tutorial and install everything exactly as shown in this below tutorial
14 May 2025 Update
Now uses between 21.5 - 22.5 GB VRAM with new added CPU offloading
Test on empty RTX 3090 ti - 4.27 second / it with LoRA
For RunPod and Massed Compute CPU offloading won't be enabled with --highvram
When using BiRefNet for removing the uploaded image background, it will use momentarily shared VRAM - so patiently wait until it is completed
Make sure to minimize your VRAM usage before running the app
Use latest installer file and delete older venv folder and run installer again
Windows:
First watch above requirements tutorial and follow every step
Extract zip archive into a drive like c:/aichar
Longer directory path or space character or special character in folder paths causes issues
Double click and install with Windows_Install.bat
Then run with Windows_Start_App.bat
If you get model download error open Windows_Start_APP.bat with a notepad editor and make "HF_HUB_ENABLE_HF_TRANSFER=0"
Massed Compute (Recommend Cloud) :
Please register via this link : https://vm.massedcompute.com/signup?linkId=lp_034338&sourceId=secourses&tenantId=massed-compute
Use our coupon SECourses
Our coupon works on all GPUs now
H100 has amazing price and speed but you can use like RTX A6000 ADA as well
Full details here : https://www.patreon.com/posts/26671823
Then select our image SECourses from Creator dropdown
Then follow Massed_Compute_Instructions_READ.txt
Same as my any other Massed Compute installer script
Example tutorial for learn how to install and use Massed Compute
(Starts at 12:58) : https://youtu.be/KW-MHmoNcqo?si=G1WbG-Qw4ujWvOtG&t=778
RunPod (Cloud):
Please register via this link : https://runpod.io?ref=1aka98lq
Then follow Runpod_Instructions_READ.txt
Same as my any other RunPod installer script
Use the template written in Runpod_Instructions_READ.txt file
Example tutorial for learn how to install and use RunPod
(starts at 22:03) : https://youtu.be/KW-MHmoNcqo?si=QN8X8Sjn13ZYu-EU&t=1323
Comments
Furkan Gözükara
let me check and fix hopefully
Błażej Porwoł
i have resolved the error with putting my own HF token in the file. however, there is another one: Loading matting model from ZhengPeng7/BiRefNet... A new version of the following files was downloaded from https://huggingface.co/ZhengPeng7/BiRefNet: - BiRefNet_config.py . Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision. A new version of the following files was downloaded from https://huggingface.co/ZhengPeng7/BiRefNet: - birefnet.py . Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision. Error loading matting model: 'Config' object has no attribute 'is_encoder_decoder'
Błażej Porwoł
when running there are multiple errors like these: Failed to download initial LoRA Makoto_Shinkai_style.safetensors: 401 Client Error. (Request ID: Root=1-68b9d702-45081a8965fb7160472b5a8b;b96fdbc8-86a5-4326-9576-3bea27bc6020) Repository Not Found for url: https://huggingface.co/InstantX/FLUX.1-dev-LoRA-Makoto-Shinkai/resolve/main/Makoto_Shinkai_style.safetensors. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. For more details, see https://huggingface.co/docs/huggingface_hub/authentication User Access Token "read_gated" is expired
Furkan Gözükara
will look at it hopefully soon
Mark Sutherland
Thank you for your work on this, Dream0 looks good too.
Furkan Gözükara
hopefully i will update this soon. currently it needs 48 gb but it will work on 24 gb. actually let me work on that now
Nobodys Hero
Lol i shall bow to your superior skillage Doc, after hours of trying toi get this optimised version working i surrender........needs your magic
Furkan Gözükara
i am following but no news yet :(
Nobodys Hero
hare we closer to the quantization Doc?
Furkan Gözükara
yes this requires 48 gb GPU atm. I am trying to reduce it to 24 GB if i can
Leonid Wolf
Hello, I tried to upload your build, but after uploading the models, I get Error initializing the main pipeline: CUDA out of memory. Tried to allocate 90.00 MiB. GPU 0 has a total capacity of 12.00 GiB of which 0 bytes is free. Of the allocated memory 26.35 GiB is allocated by PyTorch, and 5.19 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) My graphics memory is 12gb. And at the same time, at the beginning of the download, it outputs LINK : fatal error LNK1181: the input file "io.lib" cannot be opened test.c LINK : fatal error LNK1181: the input file "cufile.lib" cannot be opened
Furkan Gözükara
sadly not that i know :( we need quantization
Mika Kujanpää
Thanks! I installed this locally to Linux PC, but I think this tries to use only one GPU (I have two 24GB Nvidia). Is there a way to modify settings to use both of them?
