Loading Checkpoint Shards:耗时过长 Shards Stuck · Issue 587 · Lmsys Fastchat · Github
33%| | 1/3 [00:16<00:32, 16.31s/it]killedubuntu 内存不够，杀掉了pytorch占用太多内… It said that some weights of the model checkpoint at checkpoints were not used when initializing t5forconditionalgeneration: Same model and same machine, sometimes it takes less than 1 minute, but sometimes it takes more than 10 minutes.
Failure after loading checkpoint shards. · Issue 655
复现方法 | steps to reproduce. Loading checkpoint shards is very slow. Load the model once in a jupyter notebook cell, and run the generation in a separate cell.
This was working correctly but now it gets stuck at loading the model from cache apparently.
To load a lightningmodule along with its weights and hyperparameters use the following method: To change the checkpoint path use the default_root_dir argument: Have a question about this project? I'm wondering if it's caused by pipe.enable_model_cpu_offload()?
and the output of the model is really a mess. This way, you load the model only once, speeding up the process. When working with large models in pytorch lightning,. With distributed checkpoints (sometimes called sharded checkpoints), you can save and load the state of your training script with multiple gpus or nodes more efficiently, avoiding memory.
提示工程L1：关键原则_loading checkpoint shards 0CSDN博客
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Is there any way that checkpoint shards can maybe be cached or. Assuming you are trying to load a pretrained checkpoint, which can be.
Failure after loading checkpoint shards. · Issue 655
CPU模式下，Loading checkpoint shards只能加载到43 · Issue 3393 · chatchatspace
Loading checkpoint shards stuck · Issue 587 · lmsys/FastChat · GitHub
Loading checkpoint shards failed · Issue 7 · THUDM/ChatGLM6B · GitHub
