Building a Vision App with Ollama Structured Outputs
In this video, I look at the Ollama structured outputs and how you can use it to do various tasks, such as named entity recognition and information extractio...
DSPy Documentation
The framework for programming—rather than prompting—language models.
GitHub - ErikBjare/gptme: Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web, vision.
Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web, vision. - ErikBjare/gptme
marimo v0.9.0 with mo.ui.chat
The latest release of the Marimo Python reactive notebook project includes a neat new feature: you can now easily embed a custom chat interface directly inside of your notebook. Marimo …
pytudes/ipynb/CherylMind.ipynb at main · norvig/pytudes
There has been much debate on the degree to which Large Language Models (LLMs) have a theory of mind: a way of understanding what other people know and don't know. In this notebook I explore one small part of the issue by asking nine LLM chatbots to solve the Cheryl's Birthday Problem, a well-known logic puzzle in which different characters have different states of knowledge at different times.
mlx-vlm
The MLX ecosystem of libraries for running machine learning models on Apple Silicon continues to expand. Prince Canuma is actively developing this library for running vision models such as Qwen-2 …
GitHub - divelab/DIG: A library for graph deep learning research
A library for graph deep learning research. Contribute to divelab/DIG development by creating an account on GitHub.
light-the-torch
`light-the-torch` is a small utility that wraps `pip` to ease the installation process for PyTorch distributions like `torch`, `torchvision`, `torchaudio`, and so on as well as third-party packages that …
leapingio/leaping
Leaping's pytest debugger is a simple, fast and lightweight debugger for Python tests. Leaping traces the execution of your code and allows you to retroactively inspect the state of your program at any time, using an LLM-based debugger with natural language.
It does this by keeping track of all of the variable changes and other sources of non-determinism from within your code.
Code LoRA from Scratch - a Lightning Studio by sebastian
LoRA (Low-Rank Adaptation) is a popular technique to finetune LLMs more efficiently.
This Studio explains how LoRA works by coding it from scratch, which is an excellent exercise for looking under the hood of an algorithm.
srush/MiniChain: A tiny library for coding with large language models.
A tiny library for coding with large language models. - srush/MiniChain: A tiny library for coding with large language models.
jackmpcollins/magentic: Seamlessly integrate LLMs as Python functions
Seamlessly integrate LLMs as Python functions. Contribute to jackmpcollins/magentic development by creating an account on GitHub.
Jupyter AI — Jupyter AI documentation
TensorFlow with GPU support on Apple Silicon Mac with Homebrew and without Conda / Miniforge | by Søren L Kristiansen | Medium
minimaxir/simpleaichat: Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
simpleaichat is a Python package for easily interfacing with chat apps like ChatGPT and GPT-4 with robust features and minimal code complexity. This tool has many features optimized for working with ChatGPT as fast and as cheap as possible, but still much more capable of modern AI tricks than most implementations:
Create and run chats with only a few lines of code! Optimized workflows which minimize the amount of tokens used, reducing costs and latency. Run multiple independent chats at once. Minimal codebase: no code dives to figure out what's going on under the hood needed! Chat streaming responses and the ability to use tools. Async support, including for streaming and tools. Ablity to create more complex yet clear workflows if needed, such as Agents. (Demo soon!) Coming soon: more chat model support (PaLM, Claude)!
Scikit-LLM: Sklearn Meets Large Language Models | Macs in Chemistry
Seamlessly integrate powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
Pandas AI: The Generative AI Python Library - KDnuggets
The road to simpler Data Analysis for data scientists and analysts, powered by OpenAI.
albumentations-team/albumentations: Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 -...
Set Up Python Environment for CogSci 131
CogSci 131 (Computational Modeling of Cognition) is one of my favorite classes at Berkeley when I took it with Prof. Tom Griffiths in 2016. Now I’m teaching it in my last semester. Before getting to the fun parts (e.g., implementing recurrent nets and classic RL algorithms like SARSA using vanilla NumPy), one needs to set up the right Python environment. I hope this tutorial can save students some headaches.
Option #1: Conda Virtual Environment To avoid nightmares down the line👇, use virtual environments for your local stuff.
Instructions to install TensorFlow in a Conda Environment · Issue #153 · apple/tensorflow_macos
This is not so much an issue as opposed to a 'How To' if you'd like to install this version of Tensorflow in Conda. Prerequisites: You must be on macOS Big Sur If you have a...
slundberg/shap: A game theoretic approach to explain the output of any machine learning model.
A game theoretic approach to explain the output of any machine learning model. - slundberg/shap: A game theoretic approach to explain the output of any machine learning model.
Google Colaboratory
Machine Learning with Python: from Linear Models to Deep Learning | edX
An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. -- Part of the MITx MicroMasters program in Statistics and Data Science.
Deepnote - Data science notebook for teams
Fully managed data science notebooks that work well in a team.