Re:Show HN: finetune LLMs via the Finetuning Hub
by vorticalbox on Monday September 04, 2023 @05:39PM
(#37385358)
This is actually what I was hoping for. For Web UI that you can load a model then load some data and hit train.
You can do this in the stable defusion UI to fine tune models with your own dataset
Re:Show HN: finetune LLMs via the Finetuning Hub
by mikeravkine on Monday September 04, 2023 @06:58PM
(#37385974)
OobaBooga supports this kind of load-and-go LORA: https://github.com/oobabooga/text-generation-webui
Re:Show HN: finetune LLMs via the Finetuning Hub
by rsaha7 on Wednesday September 06, 2023 @08:56PM
(#37413436)
Looked at the project. Great initiative.
Re:Show HN: finetune LLMs via the Finetuning Hub
by rsaha7 on Wednesday September 06, 2023 @08:56PM
(#37413434)
Feedback taken. We are working on making it more explicit for users to mention the task and dataset they want to train models on. Additionally, we will introduce a flag to let people mention the prompt they want to use for finetuning these models.
Re:Show HN: finetune LLMs via the Finetuning Hub
by Charon77 on Wednesday September 06, 2023 @07:22PM
(#37412744)
It's hardcoded, hidden within the code there are calls to huggingface's datasets.load_dataset, but you don't get to specify on your own..
Re:Show HN: finetune LLMs via the Finetuning Hub
by rsaha7 on Wednesday September 06, 2023 @08:55PM
(#37413429)
Great observation. We are working on making this part very explicit. The goal was to let researchers get up to speed with the codebase to begin with, and then they would understand what needs to change to make these models work on custom datasets.
That being said, we are working on adding instructions to specify dataset and also the prompt that users want to use.
Re:Show HN: finetune LLMs via the Finetuning Hub
by rsaha7 on Wednesday September 06, 2023 @08:53PM
(#37413420)
You are right in that the loading is right now on huggingface’s dataset. The feedback about it being opaque has merit, and we are working on giving users more control and visibility into the dataset loading. To your point, adding instructions about how one can load their own dataset and do fine-tuning can assist researchers better in leveraging these models. That being said, the README under each model folder has all the info one needs to get started.
More than happy to have you contribute to the repo. There’s a lot of exciting work to be done.
I think a lot of people what something like... "drop .txt files of example data to train on in this /folder/ and run python finetune.py /folder/