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A latent text-to-image diffusion model
Python Data Science Handbook: full text in Jupyter Notebooks
Learn how to develop, deploy and iterate on production-grade ML applications.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
🔊 Text-Prompted Generative Audio Model
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Instruct-tune LLaMA on consumer hardware
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
StableLM: Stability AI Language Models
QLoRA: Efficient Finetuning of Quantized LLMs
Public facing notes page
Official inference library for Mistral models
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Using Low-rank adaptation to quickly fine-tune diffusion models.
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
Collection of notebooks about quantitative finance, with interactive python code.
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Accepted as [NeurIPS 2024] Spotlight Presentation Paper
Portfolio and risk analytics in Python
A scikit-learn compatible neural network library that wraps PyTorch
Efficient Image Captioning code in Torch, runs on GPU
Create delightful software with Jupyter Notebooks
Technical Analysis Library using Pandas and Numpy
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Jupyter notebooks for the Natural Language Processing with Transformers book