Nerlnet is a framework for research and development
Technical principles related to large models
The Logfire MCP Server is here
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models
Simple, Pythonic building blocks to evaluate LLM applications
Android Application Identifier for Packers, Protectors and Obfuscators
Open source driver assistance system
DoWhy is a Python library for causal inference
AutoML library for deep learning
DeepSeek Coder: Let the Code Write Itself
A Binary Ninja plugin, MCP server
Scalable data pre processing and curation toolkit for LLMs
A Python package for segmenting geospatial data with the SAM
Explainability and Interpretability to Develop Reliable ML models
Data science spreadsheet with Python & SQL
Industrial-strength Natural Language Processing (NLP)
Deep universal probabilistic programming with Python and PyTorch
RL research on Android devices
Underthesea - Vietnamese NLP Toolkit
Python library for Representation Learning on Knowledge Graphs
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
Speech-to-text, text-to-speech, and speaker recognition
Synchronized Translation for Videos
Reference PyTorch implementation and models for DINOv3