大模型api中转站

The Summarizer API summarizes a given body of text via a browser's internal AI model (which may differ between browsers).

文｜coco酱 2022年4月，谷歌发布了一个基于 Pathways 架构的、拥有 5400 亿参数的超大语言模型，命名为 PaLM，即 Pathways Language Model。 就在昨天，谷歌突然宣布开放其PaLM API服务，让开发者能够使用其最先进的 AI 语言模型之一：PaLM，赋能

The URL API is a component of the URL standard, which defines what constitutes a valid Uniform Resource Locator and the API that accesses and manipulates URLs. The URL standard also defines concepts such as domains, hosts, and IP addresses, and also attempts to describe in a standard way the legacy application/x-www-form-urlencoded MIME type used to submit web forms' contents as a set of key/value pairs.

LocalAI 是一个用于本地推理的 与OpenAIAPI 规范兼容的REST API， 它允许使用消费级硬件在本地或本地运行模型，支持llama.cpp、alpaca.cpp、gpt4all.cpp、rwkv.cpp、whisper.cpp、vicuna、koala、gpt4all-j、cereb

The Streams API allows JavaScript to programmatically access streams of data received over the network and process them as desired by the developer.

大家千呼万唤的新版API，它终于来了！九月底上线，上线当晚调用次数就已破千，一周过万，好评如潮。 这一版API将6大3D轻量化处理接口进行统筹，同时开放了更大在线模型接口，可支持10余种格式模型上传，满足了用户批量处理模型、快速开发的深度应用需求。 新版API自上线以来，在智慧园区、电商、工业等领域

The Presentation API lets a user agent (such as a Web browser) effectively display web content through large presentation devices such as projectors and network-connected televisions. Supported types of multimedia devices include both displays which are wired using HDMI, DVI, or the like, or wireless, using DLNA, Chromecast, AirPlay, or Miracast.

在Python中把机器学习模型转成API API简介 Flask基础 构建机器学习模型 保存机器学习模型——序列化和反序列化 用Flask为模型创建API 在Postman中测试API API简介 简单来说，API其实就是两个软件之间的接口，如果面向终端用户的软件能以预定义的格式提供输入，另一个软件

The Beacon API is used to send an asynchronous and non-blocking request to a web server. The request does not expect a response. Unlike requests made using XMLHttpRequest or the Fetch API, the browser guarantees to initiate beacon requests before the page is unloaded and to run them to completion.

最近在做机器学习系统，模型训练好了，API也开发完了，目前使用的API服务套件是：fastapi + gunicorn +docker。 但是有一个问题一直没有解决，就是当API服务启用多个worker时，一个worker会加载一次模型到内存中，内存资源的消耗非常大，如果直接这样使用，会极大的提升硬