Prodigy in 2023: LLMs, task routers, QA and plugins · Explosion

Sugarcane AI is an open-source framework designed to simplify and accelerate LLM app development. With a focus on fine-tuned Language Models (LLMs), prompt management, and Workflow Plugins, Sugarcane AI empowers developers to build, train, and manage complex LLM applications effortlessly. 🎉

Why Sugarcane AI? : Key Features of Microservices Framewor... See more

a couple of the top of my head:

• LLM in the loop with preference optimization


• synthetic data generation


• cross modality "distillation" / dictionary remapping


• constrained decoding

A rough analogy to the current LLM process is that making a new model is like baking a cake. You figure out your data and algorithms—like mixing the batter—and then you pretrain the model, that is, run it on a large number of computers for several months—like putting it in the oven—and then at the end you do some “post training”—like frosting and d... See more

OpenAI just dropped their Prompt Engineering guide. Here are 6 strategies they recommend for getting better results from LLMs:

🌳 Galileo LLM Studio

Algorithm-powered LLMOps Platform

Find the best prompt, inspect data errors while fine-tuning, monitor LLM outputs in real-time. All in one powerful, collaborative platform.

As OpenAI released smarter, more sophisticated models like GPT-3.5 and GPT-4, many of these old tricks became unnecessary. As someone who freelances as a prompt engineer and created a popular course on the topic (we just passed 50,000 students!), many people ask me if prompt engineering will even be needed in the future when GPT-5 or GPT-6 comes ou

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Introducing Prompts: LLM Monitoring

W&B Prompts – LLM Monitoring provides large language model usage monitoring and diagnostics. Start simply, then customize and evolve your monitoring analytics over time.