- Awesome GPT - GitHub
Awesome GPT A curated list of awesome projects and resources related to GPT, ChatGPT, OpenAI, LLM, and more
- GitHub - openai gpt-oss: gpt-oss-120b and gpt-oss-20b are two open . . .
Try gpt-oss · Guides · Model card · OpenAI blog Download gpt-oss-120b and gpt-oss-20b on Hugging Face Welcome to the gpt-oss series, OpenAI's open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases We're releasing two flavors of these open models: gpt-oss-120b — for production, general purpose, high reasoning use cases that fit into a single
- GPT-3: Language Models are Few-Shot Learners - GitHub
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
- GitHub - binary-husky gpt_academic: 为GPT GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读 . . .
GPT 学术优化 (GPT Academic) 如果喜欢这个项目，请给它一个Star；如果您发明了好用的快捷键或插件，欢迎发pull requests！ If you like this project, please give it a Star Read this in English | 日本語 | 한국어 | Русский | Français All translations have been provided by the project itself
- GitHub - openai gpt-2: Code for the paper Language Models are . . .
The dataset our GPT-2 models were trained on contains many texts with biases and factual inaccuracies, and thus GPT-2 models are likely to be biased and inaccurate as well To avoid having samples mistaken as human-written, we recommend clearly labeling samples as synthetic before wide dissemination
- GPT-API-free DeepSeek-API-free - GitHub
️ 免费API Key gpt-5系列模型的推理能力较弱，若需要更强的推理能力，可以购买付费API ️ 免费API Key仅可用于个人非商业用途，教育，非营利性科研工作中。
- gpt-5-chatgpt gpt-4o: gpt-4o绘图指南及国内使用gpt4o . . . - GitHub
gpt-4o绘图指南及国内使用gpt-4o方法：详细教程与案例分享【2025 09】 更新日期：2025-09-19 今天我们一起来了解一下GPT-4o技术，这是一项由OpenAI开发的AI驱动绘图工具，正在图像创作领域掀起一场革命。 借助GPT-4o的强大能力，它能够将我们的创意轻松转化为现实。
- gpt-engineer - GitHub
gpt-engineer installs the binary 'bench', which gives you a simple interface for benchmarking your own agent implementations against popular public datasets The easiest way to get started with benchmarking is by checking out the template repo, which contains detailed instructions and an agent template
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