machine-learning

spaCy-wrap is a wrapper library for spaCy for including fine-tuned transformers from Huggingface in your spaCy pipeline allowing you to include existing fine-tuned models within your SpaCy workflow.

Find the optimal model serving solution for 🤗 Hugging Face models 🚀

Getting started with Hugging Face

Datasets in kazakh language for different tasks

Introduction to MLX for Swift developers

Whispers in the Machine: Confidentiality in Agentic Systems

A practical guide to AI: from running your first local model to building your own agents. 52 files covering LLMs, Ollama, RAG, prompt engineering, machine learning, AI agents, and local AI tools.

Build LLM systems you actually control. A free, open engineering book + course — from tokenization to serving your own models. Mechanisms, trade-offs, and numbers, not prompt tips

Needle simplifies building RAG pipelines.

APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily

An implementation of Conformer: Convolution-augmented Transformer for Speech Recognition, a Transformer Variant in TensorFlow/Keras

Interactive notes (Jupyter Notebooks) for building AI-powered applications

🤗 Push your spaCy pipelines to the Hugging Face Hub

Developed a sophisticated machine learning model capable of generating diverse interview questions aligned with specific topics, ensuring depth of conversation. Integrated advanced Natural Language Processing (NLP) algorithms to analyse spoken responses, identifying grammatical errors & offering accurate corrections after the interview.

Designing and Deploying LLM Pipelines

First open-source TurboQuant KV cache compression for LLM inference. Drop-in for HuggingFace. pip install turboquant.

Intelligent file organization with computer vision, audio analysis, chunking, proactive AI-powered analysis, interactive classification, and adaptive learning.

Simple, Composable, High-Performance, Safe and Web3 Friendly AI Agents and LazAI Gateway for Everyone

AI-powered form filling and data extraction browser extension

SentimentArcs: a large ensemble of dozens of sentiment analysis models to analyze emotion in text over time