Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Unet folder not found with GGUF nodes - case sensitive #1081

Open
F117aDriver opened this issue Jan 2, 2025 · 2 comments
Open

Unet folder not found with GGUF nodes - case sensitive #1081

F117aDriver opened this issue Jan 2, 2025 · 2 comments
Labels
bug Something isn't working

Comments

@F117aDriver
Copy link

What happened?

Running AppImage on Linux, the Unet Load (GGUF) is not able to find the model. I had to rename the "Unet" folder in the models folder to "unet" to get it to work.

Steps to reproduce

  1. Run appimage on Linux
  2. Move previously downloaded models into the folder structure created by Stability Matrix (putting GGUF models in the Unet folder)
  3. Try to use the Unet Load (GGUF) node, click on the model name input area which says "null" by default
  4. Nothing pops up
  5. Click the increment arrow on either side and the input changes from "null" to "undefined"
  6. Create a "unet" folder in the models directory and move GGUF models into it
  7. Repeat 1-5 and it will work.

Relevant logs

No response

Version

V2.13

What Operating System are you using?

Linux

@F117aDriver F117aDriver added the bug Something isn't working label Jan 2, 2025
@airtonix
Copy link

airtonix commented Jan 13, 2025

same here, looks the team develop on mac or windows so they won't notice the issue.

these paths need to be derived from config instead of hard coding them into code.

@jvcosmo
Copy link

jvcosmo commented Jan 16, 2025

try ln -s Unet unet inside the models folder.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
bug Something isn't working
Projects
None yet
Development

No branches or pull requests

3 participants