loeweX / Custom-ConvLayers-Pytorch
A reimplementation of 2D Convolutional and Transposed Convolutional Layers in PyTorch, designed for easy modifications and analysis. Includes comprehensive explanations and testing.
☆19Updated last year
Alternatives and similar repositories for Custom-ConvLayers-Pytorch:
Users that are interested in Custom-ConvLayers-Pytorch are comparing it to the libraries listed below
- ☆20Updated 9 months ago
- Understanding how features learned by neural networks evolve throughout training☆32Updated 3 months ago
- QAmeleon introduces synthetic multilingual QA data using PaLM, a 540B large language model. This dataset was generated by prompt tuning P…☆34Updated last year
- Engineering the state of RNN language models (Mamba, RWKV, etc.)☆32Updated 8 months ago
- Meta-learning inductive biases in the form of useful conserved quantities.☆37Updated 2 years ago
- An implementation of the Llama architecture, to instruct and delight☆21Updated last month
- Official code for the paper: "Metadata Archaeology"☆19Updated last year
- Minimum Description Length probing for neural network representations☆18Updated 3 weeks ago
- Sparse and discrete interpretability tool for neural networks☆58Updated last year
- reproduces experiments from "Grounding inductive biases in natural images: invariance stems from variations in data"☆17Updated 4 months ago
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆58Updated last year
- Embedding Recycling for Language models☆38Updated last year
- PyTorch implementation for "Long Horizon Temperature Scaling", ICML 2023☆20Updated last year
- ☆37Updated 10 months ago
- ☆67Updated 6 months ago
- A case study of efficient training of large language models using commodity hardware.☆68Updated 2 years ago
- A library to create and manage configuration files, especially for machine learning projects.☆76Updated 2 years ago
- ☆48Updated last year
- The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We s…☆67Updated 2 years ago
- ☆23Updated 3 years ago
- Transformer with Mu-Parameterization, implemented in Jax/Flax. Supports FSDP on TPU pods.☆30Updated 2 months ago
- PyTorch implementation for MRL☆18Updated 11 months ago
- Codes and files for the paper Are Emergent Abilities in Large Language Models just In-Context Learning☆33Updated last month
- Proof-of-concept of global switching between numpy/jax/pytorch in a library.☆18Updated 8 months ago
- A python library for highly configurable transformers - easing model architecture search and experimentation.☆49Updated 3 years ago
- Automatically take good care of your preemptible TPUs☆36Updated last year
- Building the cognitive-core to solve ARC-AGI-2☆17Updated 2 weeks ago
- ☆51Updated 8 months ago
- Usable implementation of Emerging Symbol Binding Network (ESBN), in Pytorch☆24Updated 4 years ago
- Latest Weight Averaging (NeurIPS HITY 2022)☆28Updated last year