Hello!
Could you please help me to solve the issue with running on googlecollab
I tried on Colab to run your code with the command
python main.py --DATASET IEMOCAP --CUDA True --model_checkpoint roberta-large --alpha 0.8 --NUM_TRAIN_EPOCHS 5 --BATCH_SIZE 4 via Colab terminal.
To do this, I specifically translated Colab to Python 3.7 Unfortunately, the code starts and crashes with the error No CUDA GPUs are available, although I have CUDA okay (look at the first command)
photo
Please, if you have some time, could you be so kind and help to run the code on Colab or help build the assembly for the new version of Python 3.10

I've already read an article and code in https://github.com/microsoft/K-Adapter, but last commit in there was a long time ago and I found that you also did the job
Ideally I'm trying to implement K-adapter method on arxiv dataset with some pretrained bert model, to solve Topic Modeling problem and predict categories of scientific articles based on their abstract, title, etc
If you have any suggestions, I will be very thankful
Hello!
Could you please help me to solve the issue with running on googlecollab
I tried on Colab to run your code with the command

python main.py --DATASET IEMOCAP --CUDA True --model_checkpoint roberta-large --alpha 0.8 --NUM_TRAIN_EPOCHS 5 --BATCH_SIZE 4 via Colab terminal.
To do this, I specifically translated Colab to Python 3.7 Unfortunately, the code starts and crashes with the error No CUDA GPUs are available, although I have CUDA okay (look at the first command)
photo
Please, if you have some time, could you be so kind and help to run the code on Colab or help build the assembly for the new version of Python 3.10
I've already read an article and code in https://github.com/microsoft/K-Adapter, but last commit in there was a long time ago and I found that you also did the job
Ideally I'm trying to implement K-adapter method on arxiv dataset with some pretrained bert model, to solve Topic Modeling problem and predict categories of scientific articles based on their abstract, title, etc
If you have any suggestions, I will be very thankful