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A set of Python scripts that makes your experience on TPU better
INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI
Evaluating LLMs with Dynamic Data
Implementation of MEGABYTE, Predicting Million-byte Sequences with Multiscale Transformers, in Pytorch
A simple to use pytorch wrapper for contrastive self-supervised learning on any neural network
Implementation of the transformer proposed in "Building Blocks for a Complex-Valued Transformer Architecture"
Implementation of ST-Moe, the latest incarnation of MoE after years of research at Brain, in Pytorch
Simple Docker Compose NAS featuring Sonarr, Radarr, Prowlarr, Jellyfin, qBittorrent, PIA VPN and Traefik with SSL support
Super simple MLX (apple silicon) CLIP based photo similarity web app
MTEB: Massive Text Embedding Benchmark
MiniHF is an inference, human preference data collection, and fine-tuning tool for local language models. It is intended to help the user develop their prompts into full models.
Manage a user environment using Nix [maintainer=@rycee]
eBPF-based autoinstrumentation of web applications and network metrics
PyTorch implementation of Soft MoE by Google Brain in "From Sparse to Soft Mixtures of Experts" (https://arxiv.org/pdf/2308.00951.pdf)
CLOOB Conditioned Latent Diffusion training and inference code
CLOOB training (JAX) and inference (JAX and PyTorch)