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Fit interpretable models. Explain blackbox machine learning.
Largest list of models for Core ML (for iOS 11+)
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
ImageBind One Embedding Space to Bind Them All
Ultralytics HUB tutorials and support
Open standard for machine learning interoperability
Build resilient language agents as graphs.
A community-maintained Python framework for creating mathematical animations.
Desktop app for prototyping and debugging LangGraph applications locally.
Things you can do with the token embeddings of an LLM
The home of the Jupyter notebook graph visualization widget powered by yFiles for HTML
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
Build AI Agents with memory, knowledge, tools and reasoning. Chat with them using a beautiful Agent UI.
A collection of guides and examples for the Gemma open models from Google.
The open-source adapter for working with neo4j graphs and cypher queries in jupyter notebooks leveraging the yFiles Graphs for Jupyter plugin.
Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks
The repository for all Azure OpenAI Samples complementing the OpenAI cookbook.
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Deploy your agentic worfklows to production
Guided course to crash into the most basic ML algorithms.
Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting…
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
A simple and efficient tool to parallelize Pandas operations on all available CPUs
Exploration on introducing discrete codex and raw wave decoding to realize Brain-to-Text translation.
