8bitmp3

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

mlx

MLX: An array framework for Apple silicon

mamba

Mamba SSM architecture

sentencepiece

Unsupervised text tokenizer for Neural Network-based text generation.

mlx-examples

Examples in the MLX framework

gemma.cpp

lightweight, standalone C++ inference engine for Google's Gemma models.

gemma_pytorch

The official PyTorch implementation of Google's Gemma models

narrator

David Attenborough narrates your life

gemma

Open weights LLM from Google DeepMind.

levanter

Legible, Scalable, Reproducible Foundation Models with Named Tensors and Jax

lineax

Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax

picklescan

Security scanner detecting Python Pickle files performing suspicious actions

malicious-packages

A repository of reports of malicious packages identified in Open Source package repositories, consumable via the Open Source Vulnerability (OSV) format.

llm_rules

RuLES: a benchmark for evaluating rule-following in language models

dinosaur

s2fft

Differentiable and accelerated spherical transforms with JAX

model-transparency

Supply chain security for ML

purejaxql

Simple single-file baselines for Q-Learning in pure-GPU setting

folx

Implementation of Forward Laplacian algorithm in JAX

adversarial-random-search-gpt4

Adversarial Attacks on GPT-4 via Simple Random Search [Dec 2023]

lecture-jax.notebooks

Notebooks for the lecture-jax lecture series

day_01_exercise_intro

Exercise on an introduction to the python development framework.

day_02_exercise_optimization

Exercise on gradient descent by hand and via autograd in Jax.

day_03_exercise_algebra

Exercise on basics of algebra, curve fitting and singular value decomposition.

day_04_exercise_statistics

Exercise on statistics and distributions: mean and variance, correlation, gaussians.

day_05_exercise_neural_networks

Exercise on the MNIST-data set, artificial neurons, forward and backward pass.

day_06_exercise_cnn

Exercise on the convolution operation and convolutional neural networks.

day_07_exercise_brain_decode

Exercise on convolutional neural networks about how use them to decode brain waves.

day_08_exercise_interpretability

Exercise on interpretability with integrated gradients.

day_09_exercise_sequence_processing

Exercise on generative language modelling in Jax.