Lightning-AI / Lightning-AI/litgpt
Finetune LLM model for Classification task
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- Dominant language
- Python
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Description
I am following your book content *Build a Large Language Model (From Scratch)*
Its really great if anybody want to get
https://www.amazon.com/Build-Large-Language-Model-Scratch/dp/1633437167
I did not find much resources / examples for classification fine tuning using litgpt let me know if you have made?
1) How to change final layer from vocab size to 2 for spam message spam classification
2) How to adjust code for data with Text and Labels instead of json type custom dataset for instruction
which files i need to modified to get results
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
No files, tests, or entry points are named in the issue. Begin by locating LitGPT's fine-tuning and custom-dataset entry points, then determine whether classification fine-tuning is documented or supported; done means a reproducible spam-classification example explains the two-class output and Text/Labels data path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100