Comments (3)
BenjaminBossan
commented on June 10, 2024
I'm pretty sure that the issue you see is not PEFT-related. If you remove the PEFT part, I expect the same type of error to occur. Most likely, the issue is that you try to use Trainer with a pandas DataFrame. I'm not super knowledgeable on Trainer, but I would be surprised if that worked. Check the docs for this argument.
If you have tabular data, I don't think AutoModelForSequenceClassification is a good fit anyway. If it's pure text data, I wouldn't load it as a DataFrame.
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fishroll23
commented on June 10, 2024
Thanks for answer, I try to use datasets.Dataset instead of Dataframe in Trainer and figure it out.
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BenjaminBossan
commented on June 10, 2024
Good luck. I'll close the issue for now, as it seems to be unrelated to PEFT. Feel free to re-open if you encounter a PEFT error.
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Related Issues (20)
- TypeError: unsupported operand type(s) for *: 'Parameter' and 'NoneType' HOT 1
- Add support for OpenELM LoRA fine-tuning HOT 2
- Initialization for LoRA weights A and B initialized HOT 1
- Delete certain layers from PEFT model. HOT 6
- DoRA training in distributed setting
- Reproducibility when using a model with batch norm
- FSDP Dora/QDora Broken HOT 4
- CUDA kernels from PEFT v0.11.0 breaks C++ compilation HOT 4
- Adapter Merge for Idefics2 HOT 2
- `AdaLoRA` is incompatible with `gradient checkpointing` when using `torchrun` HOT 2
- LoRA adaptation shape mismatch HOT 7
- cannot import name 'get_peft_config' from 'peft' (unknown location) HOT 1
- how to fine tune LoRA HQQ? HOT 1
- How to finetune embeddings and LM head as a single layer when they are tied? HOT 1
- Help with : LoRA issue in distributed setting HOT 2
- ImportError with pkg_resources and packaging in PEFT when using setuptools >= 70.0.0 HOT 2
- High loss when init with `AdaLora` HOT 3
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