Popular GitHub Repositories for Adapters Layer

The Memory layer for AI Agents

This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.

Supercharge Your LLM with the Fastest KV Cache Layer

LiveStore is a next-generation state management framework based on reactive SQLite and built-in sync engine.

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

Keras Attention Layer (Luong and Bahdanau scores).

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

An AI memory layer with short- and long-term storage, semantic clustering, and optional memory decay for context-aware applications.

MemoRizz: A Python library serving as a memory layer for AI applications. Leverages popular databases and storage solutions to optimize memory usage. Provides utility classes and methods for efficient data management, including MongoDB integration and OpenAI embeddings for semantic search capabilities.

Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters).

Implementation of the Point Transformer layer, in Pytorch

Draw multi-layer neural network in your browser

Building Convolutional Neural Networks From Scratch using NumPy