conda install cuda-nvcc 如果报错了,换成 conda install cuda-nvcc -c conda-forge 就能正确安装flash-attn了。 还有一些办法,例如 去网站https://github.com/Dao-AILab/flash-attention/releases下载正确版本的whl文件,再pip install *.whl。 总之,都是cuda版本的问题,请务必注意。
flash_attn_2_cuda是一个CUDA扩展模块,因此需要确保你的系统上安装了正确的CUDA版本,并且CUDA环境变量已正确设置。 你可以通过运行nvcc --version来检查CUDA的版本。 确保CUDA的bin目录和lib目录已经添加到系统的PATH环境变量中。 尝试重新安装或编译flash_attn_2_cuda模块: 如果你是从源代码编译这个模块的,尝试重新...
whereupon the built conda packages will be available for everybody to install and use from theconda-forgechannel. Note that all branches in the conda-forge/flash-attn-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches...
Once the conda-forge channel has been enabled, flash-attn can be installed with conda: conda install flash-attn or with mamba: mamba install flash-attn It is possible to list all of the versions of flash-attn available on your platform with conda: conda search flash-attn --channel conda...
一台服务器如果是多个人在用,不管是否具备root权限,都不方便修改cuda version。 而比如下载flash-attn时,要求cuda版本大于11.6,而服务器的cuda版本为11.4,因此需要在自己的conda环境中配置一个版本大于11.6的…
attn_bias : <class 'NoneType'> p : 0.0 `flshattF` is not supported because: xFormers wasn't build with CUDA support Operator wasn't built - see `python -m xformers.info` for more info `tritonflashattF` is not supported because: xFormers wasn't build with CUDA support requires A1...
()) print(torch.__version__) print(torch.version.cuda) 安装unsloth: pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git" pip install --no-deps trl peft accelerate bitsandbytes xformers "flash-attn>=2.6.3" einops 解压训练包: unzip -O CP936 finetune_...
()) print(torch.__version__) print(torch.version.cuda) 安装unsloth: pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git" pip install --no-deps trl peft accelerate bitsandbytes xformers "flash-attn>=2.6.3" einops 解压训练包: unzip -O CP936 finetune_...
- name: flash-attn version: 2.3.6 manager: pip platform: linux-64 dependencies: torch: '*' einops: '*' packaging: '*' ninja: '*' url: https://files.pythonhosted.org/packages/3c/49/95b86adfc0d90676dcb07fcbef47c71997e6e7c9e71fda51598a962d9148/flash_attn-2.3.6.tar.gz...
5.安装flash-attention(这一步很重要,能节约大量的显存占用,我之前没装显存就爆了,一旦置换到内存就很慢了):pip install flash-attn --no-build-isolation6.修改 Janus/demo/app_januspro.py的代码:model_path = "deepseek-ai/Janus-Pro-7B" 改成 model_path = "{你下载的模型绝对路径}" 这样才不会...