- 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
- 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
- SparkGPT001 gpt-tutorial-101 - GitHub
SparkGPT001 gpt-tutorial-101 Public Notifications You must be signed in to change notification settings Fork 72 Star 393
- GitHub - karpathy minGPT: A minimal PyTorch re-implementation of the . . .
A PyTorch re-implementation of GPT, both training and inference minGPT tries to be small, clean, interpretable and educational, as most of the currently available GPT model implementations can a bit sprawling
- 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
- 可以详细说下从GPT-1到GPT-4，有哪些变化，是如何发展的？ - 知乎
GPT-3不仅能生成连贯的段落，而且能生成整篇与上下文相关、风格一致的文章，这些文章通常与人类编写的内容无法区分。 GPT-3具有零样本学习的能力，即使在没有经过特定训练的情况下，也能执行特定任务，它的出现使得AI语言模型的应用得到了广泛的推广。
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