modelscope / modelscope/DiffSynth-Studio
OOM when LORA training Wan2.2-I2V-A14B with 2-H20
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- Python
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Description
Hi all, I’m encountering OOM issues when using LoRA to finetune Wan2.2-I2V-A14B with the script lora/Wan2.2-I2V-A14B.sh on 2×80 GB H20 GPUs.
Is this expected? I noticed in the documentation that a single 80 GB GPU should be sufficient for LoRA training, so I’m wondering if I might be missing something.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with lora/Wan2.2-I2V-A14B.sh and the documentation describing single-80-GB-GPU LoRA training. Reproduce the OOM on 2×80 GB H20 GPUs, then trace the training configuration and memory use to determine whether the report reflects an incorrect expectation or a configuration problem. Done means the expected hardware requirements and any required configuration change are clearly established.
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Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100