update requirements.lock.txt

latest peft makes model.save_pretrained in finetune.py save a 443 B adapter_model.bin which is clearly incorrect (normally adapter_model.bin should > 16 MB)

update requirements.lock.txt

update requirements.lock.txt

try to lock requirements

fix

Merge branch 'main' of github.com:zetavg/llama-lora

this should be set for training

Update README.md

some fixes

update README.md

Merge branch 'dev-2'

update README.md and LLaMA_LoRA.ipynb

update

update finetune

simulate actual behavior in ui dev mode

update default branch to main

fix possible error

fix “RuntimeError: expected scalar type Half but found Float” on lambdalabs and hf

update

add cancel timeout buttons and update ui

update ui

ui fix

actual fix

position sticky

fix

ui update: debounce prompt preview events with js

add possible missing model configs and update ui

update

update

update

update

update

update

update

dry

let finetune ui support showing training progress

work on finetune ui

ui updates

build ui to load and preview train dataset

update ui

add inference_ui and stuff

add sample templates data

add llama_lora/utils/callbacks.py

add prompter from alpaca-lora

init