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## What is your question?
Dear authors, thanks a lot for this great work! I'm getting OOM while finetuning avhubert on my own dataset using multi-GPUs, and this error usually happens on non initial e…
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## ❓ Questions and Help
When I train with a single GPU, it works!
But when I want to use multi GPUs for training, there is a error(batch size, num_ workers have not changed).
Here is the specific…
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Hi, thank you for the great project.
I use two RTX2080 to train the model, but only one gpu works. I use `og_device_placement=True` and got these message:
> Device mapping:
/job:localhost/replica:0…
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Hi AlexeyAB,
When training with multi-gpus, the learning rate and batch size will increase ngpus times, I wonder why the num_batches doesn't have to decrease to 1/ngpus.
For examples, when train…
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Enabling Multi-GPU Support for SDXL
Dear developers,
I am currently using the SDXL for my project, and I am encountering some difficulties with enabling multi-GPU support. I have four Nvidia 309…
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I have 2 GPUS, each on has 24G memory.
when I run code below
`model = SentenceTransformerSpecb(
"bigscience/sgpt-bloom-7b1-msmarco",
cache_folder = "/mnt/storage/agtech/modelCache",
)
…
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It is common to use dataloader with distributed sampler when training with multi gpus. So why not use a distributed sampler in `examples/simple_trainer.py`, is that for any reason?
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Hi, I am trying to run training/evaluation with 4 A100s.
However, after some experiments I noticed that the training speed was same compared with process trained with a single GPU.
Am I missing som…
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Please refer to https://pytorch-lightning.readthedocs.io/en/latest/advanced/multi_gpu.html
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I don't find the parameter for multi-gpus training