Reverse Dependencies of einops

The following projects have a declared dependency on einops:

• llm-foundry — LLM Foundry
• LLM-keyword-extractor — This is a python package to extract keywords from a given text using LLMs
• llm-quantkit — cli tool for downloading and quantizing LLMs
• llm-rewards — Lean, modular reward functions for RL training with LLMs
• llm-rs — Unofficial python bindings for llm-rs. 🐍❤️🦀
• llm-rs-cuda — Unofficial python bindings for llm-rs.
• llm-rs-metal — Unofficial python bindings for llm-rs. 🐍❤️🦀
• llm-rs-opencl — Unofficial python bindings for llm-rs. 🐍❤️🦀
• llm-sentence-transformers — Use sentence-transformers for embeddings with LLM
• llm-serve — An LLM inference solution to quickly deploy productive LLM service
• llm-toolkit — LLM Finetuning resource hub + toolkit
• llmtuner — Easy-to-use LLM fine-tuning framework
• lm-buddy — Ray-centric library for finetuning and evaluation of (large) language models.
• lm-polygraph — Uncertainty Estimation Toolkit for Transformer Language Models
• lmetric — Large Model Metrics
• lmms-eval — A framework for evaluating large multi-modality language models
• local-attention — Local attention, window with lookback, for language modeling
• local-attention-flax — Local Attention - Flax Module in Jax
• local-attention-tf — Local attention, window with lookback, for Image, Audio and language modeling
• locking-activations — Locking activations via k-sparse autoencoders.
• logavgexp-pytorch — LogAvgExp - Pytorch
• logix-ai — AI Logging for Interpretability and Explainability
• long-short-transformer — Long Short Transformer - Pytorch
• LongNet — LongNet - Pytorch
• Lossless-BS-RoFormer — Lossless BS-RoFormer - Band-Split Rotary Transformer for SOTA Music Source Separation
• lslcharge — A deep learning toolkit for proteomics, equipped with a few tools for network recycling.
• lsts — A lightweight, fast, advanced deep learning time series package for long and short-term forecast and missing value imputation of land surface variables.
• luffy — Deep Learning - Pytorch
• lumiere — Paper - Pytorch
• lumiere-pytorch — Lumiere
• lvsm-pytorch — LVSM - Pytorch
• lycoris-lora — Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion
• m2pt — M2PT - Pytorch
• magic-pdf — A practical tool for converting PDF to Markdown
• magnet-pinn — This is the software package for simulating EM Fields using NNs
• magvit2-pytorch — MagViT2 - Pytorch
• make-a-video-pytorch — Make-A-Video - Pytorch
• mamba-former — Paper - Pytorch
• mamba-lens — TransformerLens port for Mamba
• mamba-r1 — Mamba R1 - Pytorch
• mambabyte — MambaByte - Pytorch
• mambatransformer — MambaTransformer - Pytorch
• mambavision — MambaVision: A Hybrid Mamba-Transformer Vision Backbone
• mambo-minhhai — A small example package
• mambular — A python package for tabular deep learning with mamba blocks.
• mammoth-nlp — Massively Multilingual Modular Open Translation @ Helsinki
• MaMMUT-pytorch — MaMMUT - Pytorch
• mantis-tsfm — Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification
• marcopolo-pytorch — MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering
• marge-pytorch — Marge - Pytorch
• marinedebrisdetector — A detector of marine debris with Sentinel-2 scenes
• marlin-pytorch — Official pytorch implementation for MARLIN.
• mase-tools — Machine-Learning Accelerator System Exploration Tools
• maskbit-pytorch — MaskBit
• maskinversion-torch — MaskInversion
• matcha-tts — 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching
• mblm — Multiscale Byte Language Model
• mcvit — Paper - Pytorch
• med-seg-diff-pytorch — MedSegDiff - SOTA medical image segmentation - Pytorch
• medim — medim is a all-in-one tool for medical image segmentation.
• MedPalm — MedPalm - Pytorch
• medvae — MedVAE is a family of six medical image autoencoders that can encode high-dimensional medical images into latent representations.
• Mega-pytorch — Mega - Pytorch
• mega-vit — mega-vit - Pytorch
• MEGABYTE-pytorch — MEGABYTE - Pytorch
• megatron-core — Megatron Core - a library for efficient and scalable training of transformer based models
• memesdb — index and search your meme stash with ai
• memformer — Memformer - Pytorch
• memorizing-transformers-pytorch — Memorizing Transformer - Pytorch
• memory-efficient-attention-pytorch — Memory Efficient Attention - Pytorch
• memos — A package for memos
• meshgpt-pytorch — MeshGPT Pytorch
• metabolism — Multi-organ metabolic analysis framework
• metaego — Official repo for Meta-models.
• metaformer-gpt — Metaformer - GPT
• MetaQ-sc — The implementation of the paper 'MetaQ: fast, scalable and accurate metacell inference via deep single-cell quantization'. Please refer to the paper and code repository (https://github.com/XLearning-SCU/MetaQ) for more details.
• metatreelib — PyTorch Implementation for MetaTree: Learning a Decision Tree Algorithm with Transformers
• metnet — PyTorch MetNet Implementation
• metnet3 — Metnet - Pytorch
• metnet3-pytorch — MetNet 3 - Pytorch
• mgqa — mgqa - Pytorch
• mh-moe — Paper - Pytorch
• microsoft-aurora — Implementation of the Aurora model
• miiiii — mechanistic interpretability of irriducible integer identifiers
• miles-credit — no summary
• mindstudio-probe — Ascend Probe Utils
• minestudio — A simple and efficient Minecraft development kit.
• minGRU-pytorch — minGRU
• mini-dust3r — Miniature version of dust3r, focused on inference
• mini-transformer — An advanced minimal transformer component framework
• minimagen — Minimal Imagen text-to-image model implementation.
• miniminiai — A mini version of fastai's miniai
• mirasol-pytorch — Mirasol - Pytorch
• MIRTorch — a PyTorch-based image reconstruction toolbox
• mist-medical — MIST is a simple, fully automated framework for 3D medical imaging segmentation.
• mist-vae — MIST: an interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis
• mistral-jax — JAX implementation of the Mistral model.
• mistral-v0.2-jax — JAX implementation of the Mistral v0.2 base model.
• mixture-of-attention — Mixture of Attention
• ml-energy — PhD work/exploration @ FEUP, PORTO