I'd like to contribute to it if you give me some guidance about the requirements! 😄

I'd like to contribute to it if you give me some guidance about the requirements! 😄

Great! I would start by looking at the inference code from one of the models (example) and seeing how the inputs need to be provided to the model. Once you've understood that, it should be reasonably straightforward to extend the training script to include these models with trust_remote_code=True

@edbeeching can also provide some guidance as he made the original implementation :)

Hi @sergiopaniego, I had a look at the modelling code of Molmo and the precessor is not quite the same as llama-vision and llava. So you may find it challenging to have a script that works for all these models.

If you would like to make a standalone script that works just for Molmo, adapted from our sft_vlm script, that would be a great first step, we can then iterate together to see if we can generalize the scripts.

It might also be good to track the transformers integration which will presumably standardise the preprocessing: huggingface/transformers#33710

Thanks a lot for the details!

I'm currently running the script as it is while trying to understand the differences compared to Molmo.
To clarify, @edbeeching the processor that you're talking about is the one in https://huggingface.co/allenai/Molmo-7B-D-0924/blob/main/preprocessing_molmo.py?
I'll try to generate first a standalone script for Molmo as you suggest 😄

@sergiopaniego

To clarify, @edbeeching the processor that you're talking about is the one in https://huggingface.co/allenai/Molmo-7B-D-0924/blob/main/preprocessing_molmo.py?

Yes that is the one.

Thanks for the reaffirmation, @edbeeching!

I've created a reproducible example on Google Colab to share the code:

Colab Notebook

Currently, I'm encountering a RuntimeError: CUDA error: device-side assert triggered.

Some details:

• I've set batch_size=1 because the processor.process function expects only one example.
• I’ve made some modifications to the collate_fn to accommodate the processor.
• I've also upgraded the transformers library to the latest version.

I’m actively investigating the issue. Do you have any suggestions on how to resolve it?

Thanks for the reaffirmation, @edbeeching!

I've created a reproducible example on Google Colab to share the code:

Colab Notebook

Currently, I'm encountering a RuntimeError: CUDA error: device-side assert triggered.

I could load the model without the error by first importing BitsAndBytesConfig from transformers in the 5th cell before adding the config

quantization_config = BitsAndBytesConfig(
        load_in_8bit=False, load_in_4bit=True
        )

Thanks for the reaffirmation, @edbeeching!
I've created a reproducible example on Google Colab to share the code:
Colab Notebook
Currently, I'm encountering a RuntimeError: CUDA error: device-side assert triggered.

I could load the model without the error by first importing BitsAndBytesConfig from transformers in the 5th cell before adding the config

quantization_config = BitsAndBytesConfig(
        load_in_8bit=False, load_in_4bit=True
        )

Could you share your reproducible example?

Could you share your reproducible example?

Sure, I've added those changes to your colab here and the rest should be the same.

Hello, do you have a timeline for this?

Could you share your reproducible example?

Sure, I've added those changes to your colab here and the rest should be the same.

I attempted to extend the notebook, but I encountered the same exception. I’m continuing to investigate the root cause.

Could you share your reproducible example?

Sure, I've added those changes to your colab here and the rest should be the same.

I attempted to extend the notebook, but I encountered the same exception. I’m continuing to investigate the root cause.

try this colab: https://colab.research.google.com/drive/1RICZvuxLJ0g6dCIkOIf0HC5J9fJGqNTU?usp=sharing
it get past the CUDA error and begins training before OOM

Hi, let me know if you would like me to take a look?

Hi @edbeeching!

Sorry for the delay. I was busy last week, but I have some additional time to dedicate this week. I've reproduced @smellslikeml's idea (https://colab.research.google.com/drive/1doT9u811J-WNCnsT6-rP9-OxnDv52M6W?usp=sharing), and I'll try to generate the PR this week. Should we wait until huggingface/transformers#33962 is completed?