Bharat-Runwal

Bharat-Runwal's Stars

• google-research/google-research

  Google Research

  Language:Jupyter Notebook34.2k7491.3k7.9k

• eriklindernoren/PyTorch-GAN

  PyTorch implementations of Generative Adversarial Networks.

  Language:Python16.4k2201564.1k

• unifyai/ivy

  The Unified AI Framework

  Language:Python14k7016.9k5.9k

• BlinkDL/RWKV-LM

  RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

  Language:Python12.6k134216859

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML11k27147944

• artidoro/qlora

  QLoRA: Efficient Finetuning of Quantized LLMs

  Language:Jupyter Notebook10k84248820

• NielsRogge/Transformers-Tutorials

  This repository contains demos I made with the Transformers library by HuggingFace.

  Language:Jupyter Notebook9.4k1384511.4k

• Uberi/speech_recognition

  Speech recognition module for Python, supporting several engines and APIs, online and offline.

  Language:Python8.4k2836062.4k

• Lyken17/pytorch-OpCounter

  Count the MACs / FLOPs of your PyTorch model.

  Language:Python4.9k29170526

• mosaicml/llm-foundry

  LLM training code for Databricks foundation models

  Language:Python4k48383526

• alpa-projects/alpa

  Training and serving large-scale neural networks with auto parallelization.

  Language:Python3.1k44297356

• salesforce/CodeT5

  Home of CodeT5: Open Code LLMs for Code Understanding and Generation

  Language:Python2.8k43169411

• he-y/Awesome-Pruning

  A curated list of neural network pruning resources.

  2.4k8728330

• IST-DASLab/gptq

  Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".

  Language:Python1.9k2949152

• real-stanford/diffusion_policy

  [RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion

  Language:Python1.5k16100294

• facebookresearch/multimodal

  TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

  Language:Python1.5k2140140

• vturrisi/solo-learn

  solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

  Language:Python1.4k11161186

• lukemelas/PyTorch-Pretrained-ViT

  Vision Transformer (ViT) in PyTorch

  Language:Python7861030127

• microsoft/Tutel

  Tutel MoE: An Optimized Mixture-of-Experts Implementation

  Language:Python724156493

• IST-DASLab/sparsegpt

  Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

  Language:Python710153295

• locuslab/wanda

  A simple and effective LLM pruning approach.

  Language:Python65096287

• cvpr2023-tutorial-diffusion-models/papers

  Language:Python2125018

• VainF/Diff-Pruning

  [NeurIPS 2023] Structural Pruning for Diffusion Models

  Language:Python16371211

• yilundu/reduce_reuse_recycle

  ICML 2023: Reduce, Reuse, Recycle: Composing Energy-Based Diffusion Models with MCMC

  Language:Jupyter Notebook1325111

• thunlp/MoEfication

  Language:Python1078710

• Picsart-AI-Research/IPL-Zero-Shot-Generative-Model-Adaptation

  [CVPR 2023] Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

  Language:Python829129

• cvlab-columbia/ZSRobust4FoundationModel

  Language:Python38372

• adapter-hub/efficient-task-transfer

  Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021

  Language:Python34314

• FrancescoSaverioZuppichini/Loading-huge-PyTorch-models-with-linear-memory-consumption

  Little article showing how to load pytorch's models with linear memory consumption

  34221

• calgaryml/condensed-sparsity

  [ICLR 2024] Dynamic Sparse Training with Structured Sparsity

  Language:Jupyter Notebook175173