Personal testbed and collection of utilities for torch-based neural net experiments.
Folder structure:
- src/ and test/ is mostly the library part.
There is a lot of work on torch Datasets, some of it is
obsoleted by torch's
DataPipes
library which i do NOT yet use. - scripts/ contains a couple of different experiments. The files are pretty similar in structure and vary in dataset, model and training details. Most of it superseded by:
- experiments/ contains new experiments based on yaml file descriptions. It's an opinionated wrapper around my Trainer class that can also run permutations of parameters and log the results.
- notebooks-cleaned/ contains the cleaned (no output) version of all the jupyter notebooks used for experimentation. Some of them are useful, some of them are collections of crap from middle-of-the-night trial-and-error sessions.
Experiments from the experiments/ folder are run in project root with:
python exp.py experiments/the-name.yml run
Create a github issue if you are interested in playing with it and need some documentation.
experiments/logs/ contains logbooks of some experiments
After the roaring success of CLIPig (ha ha) i started a version that is configured through a graphical UI instead of yaml files.
Run it with
python src/clipig
There's a small tool to put prompts into the huggingface language generators using a browser, which is much nicer than a command line interface.
python scripts/chat_lm_browser.py [--model <hf-model-name>]
# and visit http://127.0.0.1:8000
I'm currently having fun with
python scripts/chat_lm_browser.py \
--model microsoft/phi-1_5
--device auto
--bits 8
bits
reduces the precision of the weights
(doc)
which reduces memory requirements and let's you actually put some of the models
on a normal GPU.