hkproj / quantization-notesLinks
Notes on quantization in neural networks
☆103Updated last year
Alternatives and similar repositories for quantization-notes
Users that are interested in quantization-notes are comparing it to the libraries listed below
Sorting:
- ☆203Updated 9 months ago
- making the official triton tutorials actually comprehensible☆54Updated last month
- 100 days of building GPU kernels!☆508Updated 5 months ago
- LLaMA 2 implemented from scratch in PyTorch☆353Updated 2 years ago
- GPU Kernels☆198Updated 5 months ago
- LORA: Low-Rank Adaptation of Large Language Models implemented using PyTorch☆116Updated 2 years ago
- ☆173Updated last year
- A curated list of resources for learning and exploring Triton, OpenAI's programming language for writing efficient GPU code.☆417Updated 6 months ago
- Slides, notes, and materials for the workshop☆331Updated last year
- Distributed training (multi-node) of a Transformer model☆83Updated last year
- A repository to unravel the language of GPUs, making their kernel conversations easy to understand☆193Updated 4 months ago
- ☆45Updated 4 months ago
- LoRA and DoRA from Scratch Implementations☆211Updated last year
- From scratch implementation of a vision language model in pure PyTorch☆243Updated last year
- An extension of the nanoGPT repository for training small MOE models.☆195Updated 6 months ago
- Learn CUDA with PyTorch☆84Updated last week
- Code for "LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding", ACL 2024☆338Updated 5 months ago
- Complete implementation of Llama2 with/without KV cache & inference 🚀☆48Updated last year
- Notes about "Attention is all you need" video (https://www.youtube.com/watch?v=bCz4OMemCcA)☆315Updated 2 years ago
- Reference implementation of Mistral AI 7B v0.1 model.☆28Updated last year
- Recreating PyTorch from scratch (C/C++, CUDA, NCCL and Python, with multi-GPU support and automatic differentiation!)☆159Updated last year
- A repository dedicated to evaluating the performance of quantizied LLaMA3 using various quantization methods..☆195Updated 8 months ago
- This repository contains the training code of ParetoQ introduced in our work "ParetoQ Scaling Laws in Extremely Low-bit LLM Quantization"☆105Updated 4 months ago
- ☆372Updated 5 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆226Updated 5 months ago
- ☆222Updated this week
- A Simplified PyTorch Implementation of Vision Transformer (ViT)☆211Updated last year
- Prune transformer layers☆69Updated last year
- Notes about LLaMA 2 model☆68Updated 2 years ago
- All Homeworks for TinyML and Efficient Deep Learning Computing 6.5940 • Fall • 2023 • https://efficientml.ai☆182Updated last year