Hi MAGMA Team,
First of all, thank you for your outstanding work on the MAGMA model!
I’m interested in fine-tuning MAGMA on a robotics dataset for a robot manipulation task and would appreciate some guidance. Could you please advise on the best practices for fine-tuning the model for this use case?
Specifically, I’d like to know:
What preprocessing or data formatting steps are required for the dataset?
Are there any particular aspects of the architecture or training procedure that should be modified or carefully handled?
What are the key considerations or potential pitfalls to be aware of before starting fine-tuning?
Any documentation, tips, or pointers to relevant examples would be greatly appreciated.
Thank you!
Hi MAGMA Team,
First of all, thank you for your outstanding work on the MAGMA model!
I’m interested in fine-tuning MAGMA on a robotics dataset for a robot manipulation task and would appreciate some guidance. Could you please advise on the best practices for fine-tuning the model for this use case?
Specifically, I’d like to know:
What preprocessing or data formatting steps are required for the dataset?
Are there any particular aspects of the architecture or training procedure that should be modified or carefully handled?
What are the key considerations or potential pitfalls to be aware of before starting fine-tuning?
Any documentation, tips, or pointers to relevant examples would be greatly appreciated.
Thank you!