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Copy file name to clipboardExpand all lines: en/examples/pretrain_llm.md
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@@ -352,7 +352,7 @@ Inference results are as follows:
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Ensure the swanlab version is 0.3.19
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Pretraining LLMs requires significant GPU compute power and memory. This article recommends using [SwanLab Launch](/zh/api/cli-swanlab-remote-gpu) to leverage cloud GPUs for pretraining.
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Pretraining LLMs requires significant GPU compute power and memory. This article recommends using [SwanLab Launch](/en/api/cli-swanlab-remote-gpu) to leverage cloud GPUs for pretraining.
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First, upload the dataset using the `swanlab upload -n WIKI_CN WIKI_CN` command:
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Refer to the [SwanLab Launch official documentation](/zh/api/cli-swanlab-remote-gpu) to create a `swanlab.yaml` file locally and enter the following information:
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Refer to the [SwanLab Launch official documentation](/en/api/cli-swanlab-remote-gpu) to create a `swanlab.yaml` file locally and enter the following information:
You can initialize `config` using json and yaml configuration files. For details, please refer to [Create Experiment with Configuration File](/zh/guide_cloud/experiment_track/create-experiment-by-configfile).
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You can initialize `config` using json and yaml configuration files. For details, please refer to [Create Experiment with Configuration File](/en/guide_cloud/experiment_track/create-experiment-by-configfile).
-[Organization creation](/zh/guide_cloud/general/organization.md) is now fully open, with a limit of 15 people per organization
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-[Organization creation](/en/guide_cloud/general/organization.md) is now fully open, with a limit of 15 people per organization
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- Experiment names now support "duplicates" with a new experiment naming system
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## v0.3.19 - 2024.9.2
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**🚀New Features**
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- (Beta) Added cloud storage functionality for task-based training `swanlab task`, [Documentation](/zh/api/cli-swanlab-remote-gpu.html)
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- (Beta) Added cloud storage functionality for task-based training `swanlab task`, [Documentation](/en/api/cli-swanlab-remote-gpu.html)
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**Improvements**
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-[Environment] Added CPU brand recording
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**🚀New Features**
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- (Beta) Added task-based training `swanlab task` functionality
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- Added integration with `torchtune`, [Documentation](/zh/guide_cloud/integration/integration-pytorch-torchtune)
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- Added integration with `torchtune`, [Documentation](/en/guide_cloud/integration/integration-pytorch-torchtune)
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**Improvements**
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- Added `public` parameter to `swanlab.init` to set new project visibility, defaults to `False`
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-`swanlab logout`: Support logging out of SwanLab account in terminal
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**👥Integration**
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- Added integration with HuggingFace Accelerate, [Documentation](/zh/guide_cloud/integration/integration-huggingface-accelerate.md)
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- Added integration with HuggingFace Accelerate, [Documentation](/en/guide_cloud/integration/integration-huggingface-accelerate.md)
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**⚡️Improvements**
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- Improved media file upload stability
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- Optimized ultralytics integration code
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**👥Integration**
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- Integration with Stable Baseline3, [Guide](/zh/guide_cloud/integration/integration-sb3.md)
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- Integration with Stable Baseline3, [Guide](/en/guide_cloud/integration/integration-sb3.md)
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## v0.3.3 - 2024.5.22
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**👥Integration**
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- Integration with Weights & Biases, supporting wandb project conversion to `SwanLab` projects, [Guide](/zh/guide_cloud/integration/integration-wandb.md)
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- Integration with Ultralytics, [Guide](/zh/guide_cloud/integration/integration-ultralytics.md)
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- Integration with fastai, [Guide](/zh/guide_cloud/integration/integration-fastai.md)
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- Integration with Weights & Biases, supporting wandb project conversion to `SwanLab` projects, [Guide](/en/guide_cloud/integration/integration-wandb.md)
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- Integration with Ultralytics, [Guide](/en/guide_cloud/integration/integration-ultralytics.md)
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- Integration with fastai, [Guide](/en/guide_cloud/integration/integration-fastai.md)
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## v0.3.2 - 2024.5.17
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**👥Integration**
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- Integration with Tensorboard, supporting conversion of `Tensorboard` log files to `SwanLab` experiments, [Guide](/zh/guide_cloud/integration/integration-tensorboard.md)
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- Integration with Tensorboard, supporting conversion of `Tensorboard` log files to `SwanLab` experiments, [Guide](/en/guide_cloud/integration/integration-tensorboard.md)
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**🚀New Features**
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- Support for downloading line charts as PNG images
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## v0.3.0 Cloud Version Launch! - 2024.5.1
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**🚀New Features**
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- Released [Cloud Version](https://dev101.swanlab.cn)
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- Released [Cloud Version](https://swanlab.cn)
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-`swanlab.init` supports initialization with config files
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- "Environment" now records Apple M series chips
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**👥Integration**
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- Integration with 🤗HuggingFace Transformers, [Guide](/zh/guide_cloud/integration/integration-huggingface-transformers.md)
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- Integration with PyTorch Lightning, [Guide](/zh/guide_cloud/integration/integration-pytorch-lightning.md)
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- Integration with 🤗HuggingFace Transformers, [Guide](/en/guide_cloud/integration/integration-huggingface-transformers.md)
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- Integration with PyTorch Lightning, [Guide](/en/guide_cloud/integration/integration-pytorch-lightning.md)
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- Integration with Jupyter Notebook
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- Integration with Hydra, [Guide](/zh/guide_cloud/integration/integration-hydra.md)
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- Integration with Hydra, [Guide](/en/guide_cloud/integration/integration-hydra.md)
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**⚡️Improvements**
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- Optimized line chart rendering for large datasets
Copy file name to clipboardExpand all lines: en/guide_cloud/integration/integration-xtuner.md
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```
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For other integration methods with the MM series and more flexible configurations, please refer to [MMEngine Integration with SwanLab](https://docs.swanlab.cn/zh/guide_cloud/integration/integration-mmengine.html).
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For other integration methods with the MM series and more flexible configurations, please refer to [MMEngine Integration with SwanLab](https://docs.swanlab.cn/en/guide_cloud/integration/integration-mmengine.html).
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