Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix issue #32518: Update llm_tutorial.md #32523

Merged
merged 1 commit into from
Aug 8, 2024
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/source/zh/llm_tutorial.md
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ rendered properly in your Markdown viewer.

LLMs,即大语言模型,是文本生成背后的关键组成部分。简单来说,它们包含经过大规模预训练的transformer模型,用于根据给定的输入文本预测下一个词(或更准确地说,下一个`token`)。由于它们一次只预测一个`token`,因此除了调用模型之外,您需要执行更复杂的操作来生成新的句子——您需要进行自回归生成。

自回归生成是在给定一些初始输入,通过迭代调用模型及其自身的生成输出来生成文本的推理过程。在🤗 Transformers中,这由[`~generation.GenerationMixin.generate`]方法处理,所有具有生成能力的模型都可以使用该方法。
自回归生成是在给定一些初始输入,通过迭代调用模型及其自身的生成输出来生成文本的推理过程。在🤗 Transformers中,这由[`~generation.GenerationMixin.generate`]方法处理,所有具有生成能力的模型都可以使用该方法。

本教程将向您展示如何:

Expand Down