Comments (6)
@reciprocated and @Dahoas have the deepspeed configuration. Will have it merged. We usually use stage 2 though.
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#34 (comment) This accelerate config works. Typically we don't use custom deepspeed configurations unless multinode is required. If you want more hands on debugging from our engineers, happy to connect you to MLOPs/REs in Carper. Feel free to join the discord and debug me, we actively try to support all academic use cases of the API :)
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Resolved?
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Can the discord link be posted here?
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https://discord.gg/canadagoose
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Thanks, joined.
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Related Issues (20)
- multigpu support for summarization ppo example HOT 3
- Support parallel reward_fn in PPO training
- resume_from_checkpoint doesn't work HOT 1
- Issue since most recent transformers update HOT 1
- Multi-GPU training errors with peft HOT 1
- Attention mask when calculating log ratio for PPO
- when i use trlx ppotrainer train a model llama 13b model, but saved huggingface mode ,but when it inference , it has some strange keys ,and the inference result did not show ,it also have no error , it seems the result disapper HOT 1
- MPT is not working
- Runtime error when running examples (ilql_sentiments_t5.py) HOT 2
- Integration of Self-Play Fine-Tuning (SPIN) Method for Enhancing Large Language Models
- RLHF text summarization diverges
- [New Feature Request] Add KTO
- Issue of tensors share memory HOT 2
- TRLX Environment customization
- Why train dataloader is not prepared by Accelerator
- Data Loader Bug when running t5_summarization_daily_cnn.py
- Crash when using save_state with deepspeed: `model.state_dict` functions incompatible with new deepspeed.
- Error when running Ray Tune to launch hyperparameter sweep HOT 1
- maybe bug in prepare & load's order HOT 1
- cannot import name 'flatten_dataclass' from 'trlx.data.ilql_types'
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