Comments (5)
Thanks a lot to the authors for the wonderful work. I have some quick questions about the repo.
When installing causal-conv1d and mamba, I encountered an error saying "The detected CUDA version (12.3) mismatches the version that was used to compile PyTorch (11.8). Please make sure to use the same CUDA versions.". Do you know how to address it?
I also tried several different torch and cuda versions (eg tc211+cu121), it seems that sometimes it can be successfully installed but the model training become quite slow. Did you find similar issues about that, or does this repo have a strict constraint of the torch and cuda versions?
I met the same problem with you (cuda version is 12.2 + cu11.8),do you successfully train the model with CUDA version (12.3)+ cu121
from vim.
Me neither, seems this repo has a very strict constraint that the CUDA Version Must be 11.8.
from vim.
Me neither, seems this repo has a very strict constraint that the CUDA Version Must be 11.8.
I don't think so. If you install caual-conv1d and mamba whthin this repo's directory and don't use compiled whl to install, I worked on cuda11.7.
from vim.
Same here, looks like only using their provided causal-conv1d and mamba can train the model, so it needs to meet very strict requirement of cuda version
from vim.
Me neither, seems this repo has a very strict constraint that the CUDA Version Must be 11.8.
I don't think so. If you install caual-conv1d and mamba whthin this repo's directory and don't use compiled whl to install, I worked on cuda11.7.
Hi, did you install the mamba library using the setup.py file in the corresponding folder? What torch version are you using under cuda11.7?
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Related Issues (20)
- Has anyone tried utilizing FSDP (Fully Sharded Data Parallel) for Vim?
- About data flipping HOT 1
- Difference between the checkpoints? HOT 4
- "import causal_conv1d_cuda" can't find this package HOT 2
- 加载预训练模型时怎样设置通道数为4而不报错呢 HOT 2
- Does the computer have to be linux?
- Downsampling operation and how to use vim as a backbone HOT 3
- What's the meaning of self.if_bidirectional HOT 1
- Why repeat the backward block?
- correction for Env. for pretrained
- There are two same "if" code in the models_mamba.py
- import causal_conv1d_cuda出现错误 HOT 1
- mamba_simple.py里的mamba模型报错
- train problem
- Vim-Base?
- Problem about selective_scan_interface.py line 177 :conv1d_out = causal_conv1d_cuda.causal_conv1d_fwd(x, conv1d_weight, conv1d_bias,None, True) HOT 2
- Why do you still add \( T_{l-1} \) when this addition process is already included in \( V_{im} \)?
- Will Mamba2 be integrated in vim? HOT 3
- CPU Memory Usage
- Regarding the gating issue
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