System Info
transformers==4.57.1
Python==3.12.12
Kaggle env
Who can help?
@Cyrilvallez
@3outeille
Information
Tasks
Reproduction
I am developing a notebook that runs the Molmo2 - action recognition and video understanding LLM model - on Kaggle. This setup will allow users with limited computational resources to run a demo on Kaggle's GPU for free. Kaggle provides an environment with 2 NVIDIA T4 GPUs. I have manually mapped the layers across each GPU to ensure that they fit within the VRAM constraints. However, I am experiencing extremely poor model performance, as it seems to operate as if the checkpoints were not loaded correctly.
On a single GPU or CPU, the model functions properly and produces expected results. Could someone please review my notebook and suggest a solution to this issue? Your help would be greatly appreciated.
Link to my notebook.
What I have already tried:
-
Used the load_in_8bit parameter, but when I called the generate function, I encountered a NotImplementedError, so I reverted back to using torch.float16.
-
Couldn't use torch.float32 because the T4 GPU does not have enough memory.
-
Tried using the argument device_map="auto", but the mapping was problematic, as half of a block stayed on one device while the other half ended up elsewhere. This is an issue when residuals are involved.
Expected behavior
The model should say that there are penguins in the video.
System Info
transformers==4.57.1
Python==3.12.12
Kaggle env
Who can help?
@Cyrilvallez
@3outeille
Information
Tasks
examplesfolder (such as GLUE/SQuAD, ...)Reproduction
I am developing a notebook that runs the Molmo2 - action recognition and video understanding LLM model - on Kaggle. This setup will allow users with limited computational resources to run a demo on Kaggle's GPU for free. Kaggle provides an environment with 2 NVIDIA T4 GPUs. I have manually mapped the layers across each GPU to ensure that they fit within the VRAM constraints. However, I am experiencing extremely poor model performance, as it seems to operate as if the checkpoints were not loaded correctly.
On a single GPU or CPU, the model functions properly and produces expected results. Could someone please review my notebook and suggest a solution to this issue? Your help would be greatly appreciated.
Link to my notebook.
What I have already tried:
Used the
load_in_8bitparameter, but when I called the generate function, I encountered a NotImplementedError, so I reverted back to usingtorch.float16.Couldn't use
torch.float32because the T4 GPU does not have enough memory.Tried using the argument
device_map="auto", but the mapping was problematic, as half of a block stayed on one device while the other half ended up elsewhere. This is an issue when residuals are involved.Expected behavior
The model should say that there are penguins in the video.