> This path is an abbreviated tutorial prepared for specific activities and may not be maintained in real time. For use of Colossal-AI, please refer to other [examples](https://github.com/hpcaitech/ColossalAI/tree/main/examples) and [documents](https://www.colossalai.org/).
Welcome to the [Colossal-AI](https://github.com/hpcaitech/ColossalAI) tutorial, which has been accepted as official tutorials by top conference [SC](https://sc22.supercomputing.org/), [AAAI](https://aaai.org/Conferences/AAAI-23/), [PPoPP](https://ppopp23.sigplan.org/), [CVPR](https://cvpr2023.thecvf.com/), [ISC](https://www.isc-hpc.com/), etc.
quickly deploy large AI model training and inference, reducing large AI model training budgets and scaling down the labor cost of learning and deployment.
- Large Batch Training Optimization [[code]](https://github.com/hpcaitech/ColossalAI/tree/main/examples/tutorial/large_batch_optimizer) [[video]](https://www.youtube.com/watch?v=9Un0ktxJZbI)
- Fine-tuning and Inference for OPT [[code]](https://github.com/hpcaitech/ColossalAI/tree/main/examples/tutorial/opt) [[video]](https://www.youtube.com/watch?v=jbEFNVzl67Y)
Discussion about the [Colossal-AI](https://github.com/hpcaitech/ColossalAI) project is always welcomed! We would love to exchange ideas with the community to better help this project grow.
If you think there is a need to discuss anything, you may jump to our [Slack](https://join.slack.com/t/colossalaiworkspace/shared_invite/zt-z7b26eeb-CBp7jouvu~r0~lcFzX832w).
If you encounter any problem while running these tutorials, you may want to raise an [issue](https://github.com/hpcaitech/ColossalAI/issues/new/choose) in this repository.
[[video]](https://www.youtube.com/watch?v=dpMYj974ZIc) You should use `conda` to create a virtual environment, we recommend **python 3.8**, e.g. `conda create -n colossal python=3.8`. This installation commands are for CUDA 11.3, if you have a different version of CUDA, please download PyTorch and Colossal-AI accordingly.