Hugging Face Launches Transformers Agents

May 11, 2023#AI #模型 #助手35

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The OpenAssistant, StarCoder, and OpenAI language models allow anyone to easily create an AI intelligent agent. This agent can perform various tasks such as generating images from text, summarizing websites, and reading PDFs through interactive conversations. The agent can be built using a series of prompts and can generate Python code based on logical reasoning and understanding. It includes useful tools like document question-answering, speech-to-text, text-to-speech, text functions (classification, summarization, translation, download, question-answering), image functions (generation, conversion, captioning, segmentation, enlargement, question-answering), and video generation based on text. More details can be found in the provided documentation and online experience.

Allow everyone to easily use large language models such as OpenAssistant, StarCoder, OpenAI, etc., to quickly create an AI intelligent agent.

This agent can accept complex query information and achieve functions such as generating images from text, reading website summaries, and summarizing PDFs through dialogue.

The specific implementation can be built around a series of prompts, with the following process:

Clearly inform the agent of its main task;
Give the agent a tool;
Show examples to the agent;
Assign tasks to the agent, allowing it to generate Python code through logical reasoning and understanding of the task.

Currently, the agent has built-in multiple practical tools, including:

Document question-answering function;
Speech-to-text, text-to-speech;
Text functions (classification, summarization, translation, download, question-answering);
Image functions (generation, conversion, captions, segmentation, enlargement, question-answering);
Directly generate videos based on text, with strong scalability.

Documentation (https://huggingface.co/docs/transformers/transformers_agents)

Online experience (https://colab.research.google.com/drive/1c7MHD-T1forUPGcC_jlwsIptOzpG3hSj#scrollTo=5nEHtKNja52V)