Skills

Practical LangChain tutorials for LLM applications development

fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

llama3 implementation one matrix multiplication at a time

AI gateway and marketplace for developers, enables streamlined integration of AI features into products

Sample code and notebooks for Generative AI on Google Cloud

learn about LLMs, LLMOps, and vector DBs for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

"a collaborative benchmark intended to probe large language models and extrapolate their future capabilities"

provides an open-source base to create both specialized and general purpose chatbots for various applications

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"s

😎 Awesome list of tools and project with the awesome LangChain framework

AI-generated visualization prototyping and editing platform, support 2D, 3D models, combined with LLM(Large Language Model) for quick editing.

MCP server for Todoist integration enabling natural language task management with Claude

a tool that provides a Model Context Protocol (MCP) server for any web application with an OpenAPI specification.

Awesome Gen AI Tools: Anthropic's Prompt Engineering Interactive Tutorial

A library of shared system prompts for creating customized educational GPT agents.

Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

Minimize LLM token complexity to save API costs and model computations.

Create. Use. Share. ChatGPT prompts

"Tips and tricks for working with Large Language Models like OpenAI's GPT-4"

extending stable diffusion prompts with suitable style cues using text generation

A helper script for AUTOMATIC1111/stable-diffusion-webui. Basically a mix and match to quickly get different results without wasting a lot of time writing prompts.

Easily compute CLIP embeddings and build a CLIP retrieval system with them

A chat LLM based on the state-space model architecture

a high-speed inference engine for deploying LLMs locally