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Python training for business analysts and traders
AWS-Lambda-Env-Modeler is a Python library designed to simplify the process of managing and validating environment variables in your AWS Lambda functions.
Curated list of project-based tutorials
visually integration test your backend
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
A flexible distributed key-value datastore that supports both caching and beyond caching workloads.
Fast parallel LLM inference for MLX
A modular graph-based Retrieval-Augmented Generation (RAG) system
Codebase accompanying the Summary of a Haystack paper.
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality!
HippoRAG is a novel RAG framework inspired by human long-term memory that enables LLMs to continuously integrate knowledge across external documents. RAG + Knowledge Graphs + Personalized PageRank.
Open source Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in PyTorch, OpenCV (compiled for GPU), TensorFlow 2 for GPU, PyG and NVIDIA RAPIDS
🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.
Crawl and convert any website into clean markdown
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Claude Engineer is an interactive command-line interface (CLI) that leverages the power of Anthropic's Claude-3.5-Sonnet model to assist with software development tasks. This tool combines the capa…
A cloud-native vector database, storage for next generation AI applications
TextGrad: Automatic ''Differentiation'' via Text -- using large language models to backpropagate textual gradients.
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
Google Research
Code for Husky, an open-source language agent that solves complex, multi-step reasoning tasks. Husky v1 addresses numerical, tabular and knowledge-based reasoning tasks.
Together Mixture-Of-Agents (MoA) – 65.1% on AlpacaEval with OSS models
Recipes for shrinking, optimizing, customizing cutting edge vision models. 💜
🦜🔗 Build context-aware reasoning applications