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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
Awesome GPT - GitHub Awesome GPT A curated list of awesome projects and resources related to GPT, ChatGPT, OpenAI, LLM, and more
GitHub - MuiseDestiny zotero-gpt: GPT Meet Zotero. 🧠 Use GPT to generate reply text: support gpt-3 5-turbo and gpt-4 🏷️ Command tags: Click once to accelerate your research 💬 Ask questions about current PDF file (full-text or selected text) 💬 Ask questions about selected paper (Abstract) 📝 Summarize the selected paper into several highly condensed sentences
GPT-3: Language Models are Few-Shot Learners - GitHub 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
GitHub - openai gpt-2: Code for the paper Language Models are . . . 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
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
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