Tristano Profetto's Projects
Explaining Git and GitHub.
ChatGPT powered assistant software engineer
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
gpt4all: an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue
12 Weeks, 24 Lessons, IoT for All!
A roadmap to learn Kubernetes from scratch (Beginner to Advanced level)
A comprehensive collection of recent papers on graph deep learning
Llama 3
LLM training in simple, raw C/CUDA
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
AIOS: LLM Agent Operating System
Puzzles for training large scale machine learning models in a distributed setting on many GPU's
Running LLaMA on your local machine
LOw-Memory Optimization: more efficient LLM training
A solution to serve 1000s of Fine-Tuned LLMs in production for the cost of 1
Implementing Mamba in Rust
An overview of design pattern implementations in Python.
Machine Learning Engineering Guides and Tools
A guide to building an end-to-end ML Platform with MLFLOW: Track, train, and serve ML models seamlessly. Features MLFlow Server, UI, Training & Serving Containers, Artifact Registry, and Logging. Ideal for ML engineers & data scientists. #MLFLOW #MachineLearning #DataScience
Modin: Scale your Pandas workflows by changing a single line of code
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Using deep learning libraries to implement various network architectures optimized for different types of data (numbers, text, images).
Using tensorflow.js to enable Object Detection through the use of a client webcam
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
An open-source framework for training large multimodal models ... (Flamingo by Deepmind)
An open-source implementation of Google's PaLM models
The end-to-end platform for building voice products at scale
notes for prompt engineering