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⭐️ OpenAI Model Deprecation Guide

⭐️ OpenAI Model Deprecation Guide

In two days (i.e. Jan 4), OpenAI will retire 33 models, including GPT-3 (text-davinci-003) and various others. This is OpenAI's biggest model deprecation so far. Here's what you need to know: GPT-3 Model Retirement The text-davinci-003 model (commonly known as GPT-3) will be unavailable from Jan 4. → You must

Anyscale's OSS Models + Portkey's Ops Stack

Anyscale's OSS Models + Portkey's Ops Stack

The landscape of AI development is rapidly evolving, and open-source Large Language Models (LLMs) have emerged as a key foundation for building AI applications. Anyscale has been a game-changer here with their fast and cheap APIs for Llama2, Mistral, and more OSS models. But to harness the full potential of

OpenAI DevDay's Implications for LLM Apps in Prod

OpenAI DevDay's Implications for LLM Apps in Prod

We hosted a watch party for OpenAI's DevDay on our Discord channel and had a lot of fun discussing everything new and improved that was launched. If you're just catching up, read about all the updates here on the OpenAI website. Since we're all about LLM Apps in Production, let's

Building Production-Ready RAG Apps

Building Production-Ready RAG Apps

💡This is Portkey's first collaboration with the Hasura Team. Hasura helps you build robust RAG data pipelines by unifying multiple private data sources (relational DB, vector DB, etc.) and letting you query the data securely with production-grade controls. LLMs have been around for some time now and have shown that

GPT-4 is Getting Faster 🐇

GPT-4 is Getting Faster 🐇

Over the past few months, we've been keenly observing latencies for both GPT 3.5 & 4. The emerging patterns have been intriguing. The standout observation? GPT-4 is catching up in speed, closing the latency gap with GPT 3.5. Our findings reveal a consistent decline in GPT-4 latency. While your

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models - Summary

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models - Summary

This paper presents a method for compressing prompts in large language models (LLMs) to accelerate model inference and reduce cost. The method involves a budget controller, a token-level iterative compression algorithm, and an instruction tuning based method for distribution alignment. Experimental

Getting started with LLAMA 2

⭐️ Getting Started with Llama 2

Llama 2 is an open-source large language model (LLM) developed by Meta. See Llama 2's capabilities, comparisons, and how to run LLAMA 2 locally using Python.