同时,请留意自己的mamba或者conda有没有预设python版本,正如这里我的mamba会预设安装python 3.10的版本,此时如果我去搜索安装较低版本的pytorch和torchvision,也会出现无法install成功的可能 (your_env_name) C:\Users\your_PC_name>mamba install pytorch torchvision=0.12.0=py310_cu113 torchaudio cudatoolkit cudnn...
pip install triton==2.0.0 pip installcausal_conv1d==1.0.0 # causal_conv1d-1.0.0+cu118torch1.13cxx11abiFALSE-cp38-cp38-linux_x86_64.whl pip install mamba_ssm==1.0.1 # mmamba_ssm-1.0.1+cu118torch1.13cxx11abiFALSE-cp38-cp38-linux_x86_64.whl pip install scikit-learn matplotlib thop h5...
pip installmamba-ssm==1.0.1 然后直接使用transformers库读取预训练的Mamba-3B importtorchimportos from transformersimportAutoTokenizer from mamba_ssm.models.mixer_seq_simpleimportMambaLMHeadModel tokenizer =AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b") model =MambaLMHeadModel.from_pretrained(os....
blas-devel-3.9.0-21_win64_mkl The following packages will be UPDATED: openssl 3.2.1-hcfcfb64_1 -->3.3.0-hcfcfb64_0 pytorch 2.2.1-py3.12_cuda12.1_cudnn8_0 -->2.3.0-py3.12_cuda12.1_cudnn8_0 torchaudio 2.2.1-py312_cu121 -->2.3.0-py312_cu121 torchvision 0.17.1-py312_cu121...
conda create-n your_env_name python=3.10.13conda activate your_env_name conda install cudatoolkit==11.8-c nvidia pip install torch==2.1.1torchvision==0.16.1torchaudio==2.1.1--index-url https://download.pytorch.org/whl/cu118 conda install-c"nvidia/label/cuda-11.8.0"cuda-nvcc conda install...
conda create -n your_env_name python=3.10.13conda activate your_env_nameconda install cudatoolkit==11.8 -c nvidiapip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu118conda install -c "nvidia/label/cuda-11.8.0" cuda-nvccconda...
!pip install causal-conv1d==1.0.0!pip install mamba-ssm==1.0.1 然后直接使用transformers库读取预训练的Mamba-3B 代码语言:javascript 复制 importtorchimportos from transformersimportAutoTokenizer from mamba_ssm.models.mixer_seq_simpleimportMambaLMHeadModel ...
if "reduce_scatter_tensor" not in dir(torch.distributed): torch.distributed.reduce_scatter_tensor = torch.distributed._reduce_scatter_base# Raw operation, does not support autograd, but does support async def all_gather_raw(input_: Tensor, process_group: ProcessGroup, async_op: bool = False)...
!pip installmamba-ssm==1.0.1 然后直接使用transformers库读取预训练的Mamba-3B importtorchimportos from transformersimportAutoTokenizer from mamba_ssm.models.mixer_seq_simpleimportMambaLMHeadModel tokenizer =AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b") ...
按照网上的配置,最好是torch 2.1版本的,注:所有的安装时间偏慢, conda activate 虚拟环境名称 condainstallpytorch==2.1.1torchvision==0.16.1torchaudio==2.1.1pytorch-cuda=11.8-c pytorch -c nvidia condainstallcudatoolkit==11.8-c nvidia condainstall-c"nvidia/label/cuda-11.8.0"cuda-nvcc ...