Neural Probabilistic Text Generation 首先简要介绍一下beam search算法的基本形式,通常的概率文本生成模型在假设空间 Y:={BOS∘v∘EOS∣v∈V∗} 上定义了一个条件概率分布pθ(y∣x)=|y|∏t=1pθ(yt∣x,y<t) 其中V∗ 是词汇表 V 的克林闭包,模型的解码目标是找到似然概率最大的假设,即最大化后...
by calling [~generation.GenerationMixin.greedy_search] ifnum_beams=1anddo_sample=False contrastive ...
这个办法据说可以获得比Beam Search好很多的效果,但也有一个问题,就是这个k不太好选。 While top-k sampling leads to considerably higher quality text than either beam search or sampling from the full distribution, the use of a constant k is sub-optimal across varying contexts. 为啥呢?因为这个概率...
这个办法据说可以获得比Beam Search好很多的效果,但也有一个问题,就是这个k不太好选。While top-k sampling leads to considerably higher quality text than either beam search or sampling from the full distribution, the use of a constant k is sub-optimal across varying contexts....
搜索算法也叫搜索策略(或生成算法、decoding策略等叫法),应用在生成式模型的推理阶段,即模型在生成token的过程中需要使用特定的搜索算法来尽可能得到总体概率最大的tokens组合,具体的搜索算法包括Exhaustive search(穷举搜索), Greedy search(贪心搜索), Multinomial sampling, Beam search(束搜索), Top-K sampling, Top...
当使用流式时，并不支持使用beam search。class TextIteratorStreamer(TextStreamer): """ Stre...
开始前,我们需要先熟悉beam search技术,详见How to generate text: using different decoding methods for language generation with Transformers,或中文翻译版 不像一般的beam search,constrainedbeam search可以对生成文本施加控制,因为很多时候,...
开始前,我们需要先熟悉beam search技术,详见How to generate text: using different decoding methods for language generation with Transformers,或中文翻译版 不像一般的beam search,constrained beam search可以对生成文本施加控制,因为很多时候,我们是明确知道生成文本之中是应该包含哪些内容的。例如在神经网络机器翻译任...
To finish, let’s walk through an example of how to use beam search for text generation, inspired bySpeech and Language Processing(Jurafsky & Martin, 2023, Sec. 10.4). Suppose we have a very small vocabulary, consisting of just the words “ok” and “yes,” as well as an end-of-sequ...
Text generation models are often affected by adversarial examples, such as injecting some adversarial samples into the model and affecting the model's predictions. Researchers have proposed various adversarial training methods to improve the robustness of text generation models in NLP. However, these ...