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:whale2: pykoi: Active learning in one unified interface :ocean:!
:seedling: Installation
To get started to pykoi
, we recommend you test on an EC2 instance instance with the following config:
- EC2
g5.2x
(if you want to run a pretrained model with 7B parameters) - Deep Learning AMI GPU PyTorch 2.0.1 (Ubuntu 20.04) 20230627
- EBS: at least 100G
Once you are on your EC2 terminal, create a conda environment using:
conda create -n pykoi python=3.10 -y && source activate pykoi
Then install pykoi
and the correlated torch version.
pip3 install pykoi && pip3 install torch --index-url https://download.pytorch.org/whl/cu118
:question: How do I use pykoi
?
pykoi
is a python interface to unify your ML model development and production. You can easily get real-time user feedback and continuous improving your model.
Here are some examples of common applications:
:speech_balloon: Chatbots
- If you are on a GPU instance, check launch_app_gpu.ipynb and see how to launch a chatbot UI using multiple models, and thumb up/down the model answers side by side.
- If you are on a CPU instance, check launch_app_api.ipynb and see how to launch a chatbot UI using OpenAI or Amazon Bedrock (:woman_technologist: building now :man_technologist:), and thumb up/down the model answers side by side.
:nerd_face: Dev Setup
If you are interested to contribute to us, here are the preliminary development setup.
Backend Dev Setup
conda create -n pykoi python=3.10
conda activate pykoi
cd pykoi
pip3 install poetry
poetry install --no-root
Frontend Dev Setup
Frontend:
cd frontend
npm install vite
npm run build
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