Downloads · 30 days
0
AARon99/MedText-llama-2-70b-Guanaco-QLoRA-fp16
MedText-llama-2-70b-Guanaco-QLoRA-fp16 is a machine learning model from AARon99. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
I am learning how to make LoRAs with Oobabooga, these data are for experimental and research purposes.
Downloads · 30 days
0
Access
Public
Updated Aug 14, 2023
Repo size
1 GB
Likes
3
Public
Click a slice to open those files.
.bin1 GB · 100%
From the Hugging Face model README
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:
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