|
--- |
|
license: other |
|
--- |
|
I am learning how to make LoRAs with Oobabooga, these data are for experimental and research purposes. |
|
|
|
This is a Medical Knowledge LoRA made for use with this model: llama-2-70b-Guanaco-QLoRA-fp16 |
|
https://huggingface.co/TheBloke/llama-2-70b-Guanaco-QLoRA-fp16) (quantized and merged models coming soon). |
|
|
|
--- |
|
|
|
Model lineage: |
|
|
|
https://huggingface.co/timdettmers/guanaco-65b -> https://huggingface.co/Mikael110/llama-2-70b-guanaco-qlora -> https://huggingface.co/TheBloke/llama-2-70b-Guanaco-QLoRA-fp16 |
|
|
|
--- |
|
|
|
Training Data and Formatting: |
|
|
|
Training data are garnered from: https://huggingface.co/datasets/BI55/MedText |
|
|
|
These training data were then formatted for use with the "Raw text file" training option in the Oobabooga text-generation-webui: |
|
(https://github.com/oobabooga/text-generation-webui) |
|
|
|
Training parameters are in the training_parameters.json file and there is a screenshot of the UI with the correct settings. |
|
|
|
--- |
|
|
|
Examples and Additional Information: |
|
|
|
Check out the png files in the repo for an example conversation as well as other pieces of information that beginners might find useful. |
|
|
|
 |
|
|
|
--- |
|
|
|
Current/Future Work: |
|
|
|
1. Finish training with "Structed Dataset" I have a .json file with a structured dataset for the Guanaco model, but it takes significantly longer to process in the Oobabooga webui. |
|
2. Train the vanilla LlamaV2 70B model, with Raw and Structured data. |
|
3. Merge LoRA with LLM so you don't need to load the LoRA seperately. |
|
|
|
--- |
|
|
|
Use at own risk, I am using this repo to both organize my results and potentially help others with LoRA training. |
|
It is not the intention of this repo to purport medical information. |
|
Refer to the reference material for licensing guidance. I don't care how you use this LoRA, but you should reference the licensing requirments of the reference material if you indend on using this for anything other than personal use. |
|
|
|
I want to thank and acknowledge the hard work of the people involved in the creation of the dataset and Guanaco models/LoRA! Your work is greatly appreciated <3 |
