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您可以使用“docker images”查看您构建的自定义镜像。
labels) in enumerate(train_loader): images = images.cuda(non_blocking=True) labels = labels.cuda(non_blocking=True)
您可以使用“docker images”查看您构建的自定义镜像。
昇腾环境暂时不支持flash_attn接口 规避措施：修改dynamic_module_utils.py文件，将180-184行代码注释掉 vim /home/ma-user/anaconda3/envs/PyTorch-2.1.0/lib/python3.9/site-packages
labels) in enumerate(train_loader): images = images.cuda(non_blocking=True) labels = labels.cuda(non_blocking=True)
labels) in enumerate(train_loader): images = images.cuda(non_blocking=True) labels = labels.cuda(non_blocking=True) # Forward pass outputs
}/ train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz
POST https://endpoint/v2/{project_id}/training-jobs/2cd88daa-31a4-40a8-a58f-d186b0e93e4f/tasks/worker-0/save-image-job { "name" : "imagesave
}/ train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz
wget https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-vocab.json wget https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-merges.txt
GPU A系列裸金属服务器无法获取显卡如何解决 问题现象 在A系列裸金属服务器上使用PyTorch一段时间后，出现获取显卡失败的现象，报错如下： > torch.cuda.is_available() /usr/local/lib/python3.8/dist-packages/torch
create", "ims:images:delete", "ims:images:get", "ims:images:list", "ims:images
messages的样例如下： # body参考 # 图片存放本地示例 { "messages": [ { "role": "user", "content": "Picture 1: <img>/tmp/upload/demo.jpg</img>
cd ${container_work_dir}/InternVL/internvl_chat mkdir -p data/coco && cd data/coco # Download COCO images wget http://images.cocodataset.org
# shell pip install conda-pack conda pack -n sfs-clone-env -o sfs-clone-env.tar.gz --ignore-editable-packages Collecting packages...
def _filter(self, sample): messages = self.
def _filter(self, sample): messages = self.
def _filter(self, sample): messages = self.
(0)) top1.update(acc1[0], images.size(0)) top5.update(acc5[0], images.size(0)) # measure elapsed time
def _filter(self, sample): messages = self.
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