model-quantization
There are 29 repositories under model-quantization topic.
Efficient-ML/Awesome-Model-Quantization
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
horseee/Awesome-Efficient-LLM
A curated list for Efficient Large Language Models
datawhalechina/awesome-compression
模型压缩的小白入门教程，PDF下载地址 https://github.com/datawhalechina/awesome-compression/releases
inferflow/inferflow
Inferflow is an efficient and highly configurable inference engine for large language models (LLMs).
Efficient-ML/Awesome-Efficient-AIGC
A list of papers, docs, codes about efficient AIGC. This repo is aimed to provide the info for efficient AIGC research, including language and vision, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
sayakpaul/Adventures-in-TensorFlow-Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
RodolfoFerro/psychopathology-fer-assistant
[WINNER! 🏆] Psychopathology FER Assistant. Because mental health matters. My project submission for #TFWorld TF 2.0 Challenge at Devpost.
htqin/BiBench
[ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binarization.
htqin/QuantSR
[NeurIPS 2023 Spotlight] This project is the official implementation of our accepted NeurIPS 2023 (spotlight) paper QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution.
nbasyl/OFQ
The official implementation of the ICML 2023 paper OFQ-ViT
seonglae/llama2gptq
Chat to LLaMa 2 that also provides responses with reference documents over vector database. Locally available model using GPTQ 4bit quantization.
HaoranREN/TensorFlow_Model_Quantization
A tutorial of model quantization using TensorFlow
wlfeng0509/Awesome-Diffusion-Quantization
A list of papers, docs, codes about diffusion quantization.This repo collects various quantization methods for the Diffusion Models. Welcome to PR the works (papers, repositories) missed by the repo.
dcarpintero/ai-engineering
AI Engineering: Annotated NBs to dive into Self-Attention, In-Context Learning, RAG, Knowledge-Graphs, Fine-Tuning, Model Optimization, and many more.
frickyinn/BiDense
PyTorch implementation of "BiDense: Binarization for Dense Prediction," A binary neural network for dense prediction tasks.
medoidai/model-quantization-blog-notebooks
Notebook from "A Hands-On Walkthrough on Model Quantization" blog post.
SRDdev/Model-Quantization
Quantization is a technique to reduce the computational and memory costs of running inference by representing the weights and activations with low-precision data types like 8-bit integer (int8) instead of the usual 32-bit floating point (float32).
BjornMelin/local-llm-workbench
🧠 A comprehensive toolkit for benchmarking, optimizing, and deploying local Large Language Models. Includes performance testing tools, optimized configurations for CPU/GPU/hybrid setups, and detailed guides to maximize LLM performance on your hardware.
dwain-barnes/LLM-GGUF-Auto-Converter
Automated Jupyter notebook solution for batch converting Large Language Models to GGUF format with multiple quantization options. Built on llama.cpp with HuggingFace integration.
first-coding/VIT
This project distills a ViT model into a compact CNN, reducing its size to 1.24MB with minimal accuracy loss. ONNXRuntime with CUDA boosts inference speed, while FastAPI and Docker simplify deployment.
SIYAKS-ARES/survival-with-llms
The Ark Project: Selecting the perfect AI model to reboot civilization from a 64GB USB drive. Comprehensive analysis of open-source LLMs under extreme constraints, with final recommendation: Meta Llama 3.1 70B Instruct (Q6_K GGUF). Includes interactive tools, detailed comparisons, and complete implementation guide for offline deployment.
dslisleedh/NCNet-flax
Unofficial implementation of NCNet using flax and jax
satyampurwar/large-language-models
Unlocking the Power of Generative AI: In-Context Learning, Instruction Fine-Tuning, Reinforcement Learning Fine-Tuning, Retrieval Augmented Generation and LangGraph Workflows for AI Agents.
xhay-p/ttPG
Torch and Transformers Playground: Learn and Code Deep Learning using PyTorch and HuggingFace Transformers.
aashu-0/FineTuning_GPT2
PyTorch implementation of GPT-2 that loads pretrained weights and enables instruction fine-tuning on the Stanford Alpaca dataset.
Chenguiti6444/Vehicle_Detection_and_Classification_using_Deep_Learning
Fine-tuning Pretrained Deep Learning Models to Classify Low Quality Images of Land Vehicles. - Ajustement de modèles de deep learning préentraînés pour classifier des images faible qualité de véhicules terrestres.
harshmorya/Assignment__HB1--1
This project explores generating high-quality images using depth maps and conditioning techniques like Canny edges, leveraging Stable Diffusion and ControlNet models. It focuses on optimizing image generation with different aspect ratios, inference steps to balance speed and quality.
santidrj/model-quantization-aggregation
Replication package for the paper "Aggregating empirical evidence from data strategies studies: a case on model quantization" published in the 19th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM).