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If you use Transformers’ chat template, it will automatically apply the harmony response format. Welcome to the gpt-oss series, OpenAI’s open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases. Gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI We discuss broader societal impacts of this finding and of GPT-3 in general. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. At the same time, we also identify some datasets where GPT-3’s few-shot learning still struggles, as well as some datasets where GPT-3 faces methodological issues related to training on large web corpora.
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Additionally we are providing a reference implementation for Metal to run on Apple Silicon. If you use model.generate directly, you need to apply the harmony format manually using the chat template or use our openai-harmony package. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model. Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches. Delays can happen even when you have a great network.
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By default, gpt-engineer supports OpenAI Models via the OpenAI API or Azure OpenAI API, as well as Anthropic models. You can do this by specifying an image directory with the —-image_directory flag and setting a vision-capable model in the second CLI argument. This can be useful for adding UX or architecture diagrams as additional context for GPT Engineer. By default, gpt-engineer expects text input via a prompt file. You can do so via the –use-custom-preprompts argument.