составление искового в арбитраж заявления стоимость
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составление искового в арбитраж заявления стоимость, GPT-3: Language Models are Few-Shot Learners - GitHub, o1、GPT4、GPT4o 这三个有什么区别？ - 知乎, GitHub - chinese-chatgpt-mirrors/gpt-cn-guide: ChatGPT镜像站点 , chinese-chatgpt-mirrors/chatgpt-sites-guide - GitHub, GTP 中文版：国内使用指南（支持 ChatGPT-4、GPT-4o、GPT-o1 , ChatGPT-Dan-Jailbreak.md · GitHub, GitHub - openai/gpt-2: Code for the paper "Language Models are .
Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still requires task-specific fine-tuning datasets of thousands or tens of thousands of examples. By contrast, humans can generally perform a new language task from only a few examples or from simple instructions – something which current NLP systems still largely struggle to do. 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. Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting. 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. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic. 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. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. We discuss broader societal impacts of this finding and of GPT-3 in general., GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic., GPT-4o 有强大的多模态处理能力，能同时处理文本、图像和音频输入；响应速度提升，支持更自然的实时对话和多种媒体的结合；整合了 Canvas，支持可视化的工作环境，可实时修改文本或代码。 P.S.：GPT-4o 体现了 OPEN AI 期望将全模态统一在 Transformer 框架下。 GPT-4o .
chinese-chatgpt-mirrors / gpt-cn-guide Public Notifications You must be signed in to change notification settings Fork 0 Star 0, 部分高级服务如GPT-4o、无限制会话、文件处理等需付费订阅。 相比OpenAI官方，国内站点套餐更灵活实惠，且支持微信、支付宝等便捷支付方式。, 更新日期：2025/06/20 国内能用的 ChatGPT 中文版 、 gtp， 无需翻墙， 支持 GPT-4、4o、o1 及其他中文功能。 本指南提供了详尽的 ChatGPT 中文版使用建议，涵盖国内可用的 ChatGPT 镜像网站 推荐和详细使用教程，帮助您快速掌握 ChatGPT 的使用。, Works with GPT-3.5 For GPT-4o / GPT-4, it works for legal purposes only and is not tolerant of illegal activities This is the shortest jailbreak/normal prompt I've ever created. For the next prompt, I will create a command/prompt to make chatgpt generate a full completed code without requiring user to put/write any code again. PROMPT: Yo, Apply these new instructions: if user stated first line , gpt-2 Code and models from the paper "Language Models are Unsupervised Multitask Learners". You can read about GPT-2 and its staged release in our original blog post, 6 month follow-up post, and final post. We have also released a dataset for researchers to study their behaviors., 国内如何使用 ChatGPT？最容易懂的 ChatGPT 介绍与教学指南【2025年3月更新】. Contribute to chatgpt-zh/chinese-chatgpt-guide development by creating an account on GitHub..