[R] Build and personalize LLMs on your own data - Take back control with xTuring! Submitted by x_ml t3_124r3v0 2 years ago in MachineLearning [removed] 8 comments 36
JealousAd8448 t1_je0evw8 wrote 2 years ago Impressive work! Will check it out and try to contribute to the project 💪 Permalink 6
culebra_risa t1_je0g8qt wrote 2 years ago Wow, reducing the finetuning time from 20 hours to 20 minutes is amazing :O Permalink 5
OrionJr t1_je0iequ wrote 2 years ago Can’t seem to install deep speed on windows or wsl Permalink 2 x_ml OP t1_je0mp14 wrote 2 years ago Deepspeed doesn't work on Windows yet but we were able to install in WSL. My colleague installed deepspeed in conda and then installed our package and it seemed to work. Permalink Parent 3 subhash165 t1_je0mvvw wrote 2 years ago I was able to run it with WSL (with miniconda environment) Permalink Parent 2 JealousAd8448 t1_je0mp1z wrote 2 years ago Unfortunately deepspeed is not easy to install on windows. Just use wsl, it did not give any problem to me using conda with python 3.8 Permalink Parent 1
x_ml OP t1_je0mp14 wrote 2 years ago Deepspeed doesn't work on Windows yet but we were able to install in WSL. My colleague installed deepspeed in conda and then installed our package and it seemed to work. Permalink Parent 3
subhash165 t1_je0mvvw wrote 2 years ago I was able to run it with WSL (with miniconda environment) Permalink Parent 2
JealousAd8448 t1_je0mp1z wrote 2 years ago Unfortunately deepspeed is not easy to install on windows. Just use wsl, it did not give any problem to me using conda with python 3.8 Permalink Parent 1
sebzim4500 t1_je10iu2 wrote 2 years ago >Lower-precision fine-tuning (like INT8, INT4) How would this work? Are the weight internally represented as f16 and then rounded stochastically whenever they are used? Permalink 1
MohamedRashad t1_je12hzd wrote 2 years ago Where does the model save after finetuned in the example in the README ? Permalink 1
JealousAd8448 t1_je0evw8 wrote
Impressive work! Will check it out and try to contribute to the project 💪