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Full size image Figure 3 Bayesian 50% majority-rule consensus tree (box on the top left corner shows the topology) based on the combined cpDNA (matK + ndhF + rbcL + rps16 + trnL-F) dataset D270, with gaps treated as simple indels, showing the taxa from Nepetoideae, Viticoideae s....
When allied with physical and chemical TEM analysis of both planar and cross-sectional samples, key length scales such as grain size and the chiral variation of the magnetisation variation have been identified and measured. We present data showing the importance of the grain size (mostly < ...
We set the sequence length to 128 and find the maximum throughput by doubling the batch size until the GPUs run out of memory or the throughput drops off. The 25% sliced models achieve up to 1.55× throughput improvement over the dense model. At 50% slicing the largest models require only...
which limits the FLOPs they can add. However, large neural networks rely on hardware parallelism to keep the latency low, and adapter layers have to be processed sequentially. This makes a difference in the online inference setting where the batch size is typically as small as one. In a gene...
Chau Tran, Siddharth Khadkikar, Aleksey Porollo [PDF] A Short Survey of Viewing Large Language Models in Legal Aspect[2023]. Zhongxiang Sun [PDF] Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence[2023]. ...
To quantify the diversity of the generated training data of SimPrompt and AttrPrompt, we first show the vocabulary size of the generated dataset and the Gold dataset, which is a natural way to check the lexical diversity of datasets (Table 5). From the table, we can see that AttrPrompt ...