nullonesix Goto Github PK
Type: User
Bio: Software Developer, Hockey, Badminton, Ultimate, Chess
nullonesix's Projects
3d-pose-based-feedback-for-physical-exercises
This is the implementation of ACCV paper [3D Pose Based Feedback for Physical Exercises]
alphafold
Open source code for AlphaFold.
arbitrage
Single cryptocurrency exchange arbitrage via Bellman-Ford algorithm.
articles_on_deep_learning
Articles on deep learning.
chatgpt-tetris
Watch ChatGPT play Tetris! Implemented in Python using Pygame, OpenAI's library and OpenAI's API.
dimensionality_transformer
We increase the dimensionality of the transformer after every epoch.
dqn
Deep Q-Network (deep reinforcement learning) applied to Tetris.
efficient_zero
A quick implementation of MuZero (https://arxiv.org/abs/1911.08265) and EfficientZero (https://arxiv.org/abs/2111.00210) for the classic arcade game Asteroids.
elo
Elo-based ranking system for Jedi Academy.
gpt
A quick implementation of GPT based heavily on karpathy's nanoGPT implementation as well as the Attention is All You Need paper.
hypothesis_generation
Generate scientific hypotheses with the most information gain for the language model.
jedi_ai
A neural network that plays Jedi Knight: Jedi Academy but could easily be applied to other FPS games.
longnet
A quick implementation of LongNet based on the PaLM transformer implementation by lucidrains.
longnet-1
Implementation of plug in and play Attention from "LongNet: Scaling Transformers to 1,000,000,000 Tokens"
mp4_to_pdf
Python code to convert an mp4 of a video lecture to a pdf slide deck.
neural_network
An explanatory example of a neural network in C++.
swarms
Swarms is a modular framework that enables reliable, fast, and useful multi-agent collaboration at scale to automate real-world tasks.
tetris
A quick implementation of Tetris in Python using Pygame.
ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
variable_iterative_transformer
This is a variable iterative transformer. If its maximum output probabilities for the given batch are not all > some threshold probability, it iterates by using the output probabilities as the new input instead of evaluating the criterion until it reaches the threshold.
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