Tristan J. Legg
@tristanjlegg.bsky.social
Working on AI/ML/RL. Looking to better myself in all aspects. Probably should delete Dota. https://github.com/TristanJLegg
I first put together my Minecraft Gameplay Captioned dataset to train a model for an application. Surprised to see it’s close to 500 downloads.
huggingface.co/datasets/Tri...
Thinking about expanding it and improving the captions since people like it.
huggingface.co/datasets/Tri...
Thinking about expanding it and improving the captions since people like it.
TristanJLegg/MinecraftGameplayCaptioned · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
huggingface.co
October 27, 2025 at 1:40 PM
I first put together my Minecraft Gameplay Captioned dataset to train a model for an application. Surprised to see it’s close to 500 downloads.
huggingface.co/datasets/Tri...
Thinking about expanding it and improving the captions since people like it.
huggingface.co/datasets/Tri...
Thinking about expanding it and improving the captions since people like it.
Earlier this year I built a Deep Q-Network in C to test my deep learning skills. No external dependencies. Standard C libraries and my own code.
Code: github.com/TristanJLegg...
NN + backprop, replay buffer & target net, train/eval/save and a small RL env with renderer + Y4M video writer.
Code: github.com/TristanJLegg...
NN + backprop, replay buffer & target net, train/eval/save and a small RL env with renderer + Y4M video writer.
GitHub - TristanJLegg/dqn-from-scratch
Contribute to TristanJLegg/dqn-from-scratch development by creating an account on GitHub.
github.com
October 26, 2025 at 4:31 PM
Earlier this year I built a Deep Q-Network in C to test my deep learning skills. No external dependencies. Standard C libraries and my own code.
Code: github.com/TristanJLegg...
NN + backprop, replay buffer & target net, train/eval/save and a small RL env with renderer + Y4M video writer.
Code: github.com/TristanJLegg...
NN + backprop, replay buffer & target net, train/eval/save and a small RL env with renderer + Y4M video writer.