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Transformer Debugger (TDB) is a tool developed by OpenAI's Superalignment team with the goal of supporting investigations into specific behaviors of small language models. The tool combines automated interpretability techniques with sparse autoencoders. TDB enables rapid exploration before needing to write code, with the ability to intervene in the forward pass and see how it affects a particular
We're pleased to announce the latest iteration of Whisper, called large-v3. Whisper-v3 has the same architecture as the previous large models except the following minor differences: The input uses 128 Mel frequency bins instead of 80 A new language token for Cantonese The large-v3 model is trained on 1 million hours of weakly labeled audio and 4 million hours of pseudolabeled audio collected using
Evals provide a framework for evaluating large language models (LLMs) or systems built using LLMs. We offer an existing registry of evals to test different dimensions of OpenAI models and the ability to write your own custom evals for use cases you care about. You can also use your data to build private evals which represent the common LLMs patterns in your workflow without exposing any of that da
(This document is a preview of the underlying format consumed by ChatGPT models. As a developer, you can use our higher-level API and won't need to interact directly with this format today — but expect to have the option in the future!) Traditionally, GPT models consumed unstructured text. ChatGPT models instead expect a structured format, called Chat Markup Language (ChatML for short). ChatML doc
✨ Navigate at cookbook.openai.com Example code and guides for accomplishing common tasks with the OpenAI API. To run these examples, you'll need an OpenAI account and associated API key (create a free account here). Set an environment variable called OPENAI_API_KEY with your API key. Alternatively, in most IDEs such as Visual Studio Code, you can create an .env file at the root of your repo contai
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