Lightning-AI / Lightning-AI/litgpt
error: cannot unpack non-iterable ActionTypeHint object
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 13.7k
- Forks
- 1.5k
- Avg merge
- 15h 37m
- Merged PRs (30d)
- 1
Description
Bug description
Dear Lightning,
I'm attempting to follow a medium tutorial using my own dataset. I have downgraded lightning due to a suggestion on issue #1915. On step 3 of the tutorial, the fine-tuning step using litgpt, I receive the message "error: cannot unpack non-iterable ActionTypeHint object".
I am on Version 0.5.7 of litgpt and have train.json as well as the checkpoints/mistralai/Mistral-7B-Instruct-v0.3 folders in my working directory
Thus far, I have tried:
- Reading the finetune_lora readme
- installing litgpt[all] as suggested in your documentation, since the medium article only installed litgpt
- modifying the command in the medium article according to the documentation i.e. using:
litgpt finetune_lora checkpoints/mistralai/Mistral-7B-Instruct-v0.3 --data JSON --data.json_path train.json --data.val_split_fraction 0.2 --out_dir out/custom-model - Creating the output directories [either finetuned (medium article), or out/custom-model (documentation)] ahead of running the commands
Appreciate any help that you can provide.
What operating system are you using?
Linux
LitGPT Version
Version: 0.5.7
Contributor guide
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 by reproducing the documented litgpt finetune_lora command with train.json, the Mistral checkpoint path, and LitGPT 0.5.7. Compare the tutorial command with the finetune_lora README and the reported Lightning version. Done means identifying the compatibility cause and confirming a working command or documenting the required version or command changes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- cli, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100