You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Let's say I want to apply your fusion method to a PyTorch-based ViT implemented in a package that isn't Hugging Face. Specifically, I want to merge ViTs from the open_clip package (https://github.com/mlfoundations/open_clip). What changes do I need to make in your code to make it work?
Thank you for your great work!
Edan
The text was updated successfully, but these errors were encountered:
There are three tasks you need to do to add support for a new architecture:
Write a top-level fusion function (like this) for your architecture, that makes calls to functions in otfusion_lib.py.
Write an experiment YAML file (start from this), where you change the model type parameter to your new architecture.
Add support for your new model type parameter in the architecture-specific functions. There are a few architecture-specific functions in main.py and utils.py.
In general, I suggest you to step through the experiment we provide in debug mode, to get a good idea of how our fusion pipeline works in detail before starting to add support for a new architecture.
Hi,
Let's say I want to apply your fusion method to a PyTorch-based ViT implemented in a package that isn't Hugging Face. Specifically, I want to merge ViTs from the open_clip package (https://github.com/mlfoundations/open_clip). What changes do I need to make in your code to make it work?
Thank you for your great work!
Edan
The text was updated successfully, but these errors were encountered: