GitHub - joennlae/tensorli: Absolute minimalistic implementation of a GPT-like transformer using only numpy (<650 lines).

The markdown data presents a minimalistic implementation of a GPT-like transformer using only numpy, named Tensorli. The implementation includes automatic differentiation, a Tensorli object similar to PyTorch, simple neural network layers like Linearli, Embeddingli, MultiheadAttentionli, LayerNorm, and an Adamli optimizer. The library is designed to train and execute a GPT-like transformer model.

However, the author warns that the library is not optimized and is not meant for production or large-scale use, but rather as a learning tool. The library is inspired by minGPT and tinygrad projects. Future plans include adding Dropout and more experimental architectures. The name Tensorli comes from the author's regional dialect where "li" is a suffix used to mean "little", symbolizing the minimalistic nature of the library.

Key takeaways:

The markdown data presents a minimalistic implementation of a GPT-like transformer using only numpy, which includes automatic differentiation, Tensorli object, simple NN layers, and Adamli optimizers.
The library, although functional, is not optimized and is not intended for production or large-scale use. It is designed as a learning tool.
The library is heavily inspired by minGPT and tinygrad projects.
Future plans for the library include adding Dropout and more experimental architectures.

GitHub - joennlae/tensorli: Absolute minimalistic implementation of a GPT-like transformer using only numpy (<650 lines).

Key takeaways:

Comments (0)

Newsletter