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The paper states the following: "While the nonautoregressive model throughput is bounded to ∼ 2.8 samples/second for batch sizes bigger than 64, the autoregressive model throughput is linear in batch …
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Recently there have been papers about [non-autoregressive text generation](https://arxiv.org/abs/2102.08220), in which models generate many tokens simultaneously instead of only one. Not only does thi…
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While using cache (`past_key_values`) during speculative decoding or even autoregressive decoding, the resulting generated tokens might be somewhat weird and non-sense. Because of this behavior, specu…
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Some series might benefit from additional global endogenous terms, such as time-based indicators (year/month/weekday/holiday) or trend/spline functionality. These are "predictors" that are known at al…
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## 一言でいうと
翻訳文の単語を順番にではなく並列して出力できる機械翻訳モデル。
従来のEncoder-Decoderモデルと比べると計算スピードが大きく向上している。
スピードを向上させつつ翻訳の質を低下させないようにしており、Ro-En翻訳ではSOTA
![image](https://user-images.githubusercontent.com/9605058/32624…
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您好,我在阅读论文的过程中,有一个地方不理解,想请您指导一下。在论文中2.3中“Non-Autoregressive Combination Decoding“这一小节中有一句这样的描述”For those extreme records that have only one argument in the combinations, all predicted entities are aggr…
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I am looking into a modification of a regular masked autoregressive flow where the base distribution is an N-dimensional uniform and the first variable does not get transformed, while the rest of the …
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The form of speech_tokenizer in the open source model is onnx. If I want to train a speech_tokenizer myself, how should I do it? What can I refer to? Approximately how much data is needed?
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**Description:**
Predicting future traffic flow, which will aid in traffic management and planning. The goal is to build a model that can accurately forecast traffic flow based on historical data a…