Rope
Rope
Su, Jianlin, et al. “Roformer: Enhanced transformer with rotary position embedding.” Neurocompu
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seed-tts论文
seed-tts论文
Anastassiou, Philip, et al. “Seed-TTS: A Family of High-Quality Versatile Speech Generati
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End-to-end object detection with transformers
End-to-end object detection with transformers
Carion, Nicolas, et al. “End-to-end object detection w
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Megatron
Megatron
Shoeybi, Mohammad, et al. “Megatron-lm: Training multi-billion parameter language models us
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GPipe
GPipe
Huang, Yanping, et al. “Gpipe: Efficient training of giant neural networks using pipeline para
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参数服务器
参数服务器
Li, Mu, et al. “Scaling distributed machine learning with the parameter server.” 11th USENIX S
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CLIP
CLIP
https://arxiv.org/abs/2103.00020
Radford, Alec, et al. “Learning transferable visual models fro
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SpotTune Transfer Learning through Adaptive Fine-tuning
SpotTune: Transfer Learning through Adaptive Fine-tuning
Guo, Yunhui, et al. “Spottune: transfer lea
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Finetune网上博客
finetune网上博客
极市 花式 Finetune 方法大汇总
1. 招式1：使用Pretrain模型做约束在Finetune阶段，如果我们可用于Finetune的目标任务数据量较少时，很有可能
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Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference量化感知论文
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