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[misc] update pre-commit and run all files (#4752)

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* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
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Hongxin Liu
2023-09-19 14:20:26 +08:00
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parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
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examples/images/diffusion/README.md
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@@ -132,7 +132,7 @@ bash train_colossalai.sh
```
It is important for you to configure your volume mapping in order to get the best training experience.
1. **Mandatory**, mount your prepared data to `/data/scratch` via `-v <your-data-dir>:/data/scratch`, where you need to replace `<your-data-dir>` with the actual data path on your machine. Notice that within docker we need to transform the Windows path to a Linux one, e.g. `C:\User\Desktop` into `/mnt/c/User/Desktop`.
1. **Mandatory**, mount your prepared data to `/data/scratch` via `-v <your-data-dir>:/data/scratch`, where you need to replace `<your-data-dir>` with the actual data path on your machine. Notice that within docker we need to transform the Windows path to a Linux one, e.g. `C:\User\Desktop` into `/mnt/c/User/Desktop`.
2. **Recommended**, store the downloaded model weights to your host machine instead of the container directory via `-v <hf-cache-dir>:/root/.cache/huggingface`, where you need to replace the `<hf-cache-dir>` with the actual path. In this way, you don't have to repeatedly download the pretrained weights for every `docker run`.
3. **Optional**, if you encounter any problem stating that shared memory is insufficient inside container, please add `-v /dev/shm:/dev/shm` to your `docker run` command.