ar éis é seo a éisteacht, shíl Taoist Kongkong ar feadh fada agus athbhreithnigh sé leabhar an chlog arís, toisc go chonaic sé go cé go raibh roinnt focail ag tagairt do treachery, reproach agus evil, ní raibh sé ar intinn scold an domhain tráth an díobháil; Nuair a thagann sé i dtaca le leas agus dea-oifigigh, dea-cheart agus piety filialta an t-athair agus an mac, tá na háiteanna go léir a dhúntar go minic ag praise fóirne agus buntáiste, agus tá comhaltaí an teaghlaigh go hiomlán, nach bhfuil i ndáiríre inchomparáide le leabhair eile. Cé go bhfuil sé de chuspóir ginearálta labhairt faoi ghrá, ní bhíonn sé ach taifead fíor ar a gnóthaí, agus ní bhíonn sé
几篇论文实现代码:
《One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles》(SIGIR 2021) GitHub:https:// github.com/zhengyima/DHAP
《Learning to Track with Object Permanence》(ICCV 2021) GitHub:https:// github.com/TRI-ML/permatrack [fig3]
《JoJoGAN: One Shot Face Stylization》(2021) GitHub:https:// github.com/mchong6/JoJoGAN [fig1]
《A Static Analyzer for Detecting Tensor Shape Errors in Deep Neural Network Training Code》(2021) GitHub:https:// github.com/ropas/pytea
《Towards a Unified View of Parameter-Efficient Transfer Learning》(2021) GitHub:https:// github.com/jxhe/unify-parameter-efficient-tuning [fig2]
《PantheonRL: A MARL Library for Dynamic Training Interactions》(2021) GitHub:https:// github.com/Stanford-ILIAD/PantheonRL
《Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark》(NeurIPS 2021) GitHub:https:// github.com/iamalexkorotin/Wasserstein2Benchmark [fig4]
《Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data》(2021) GitHub:https:// github.com/sberbank-ai/Real-ESRGAN
《FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark》(2021) GitHub:https:// github.com/mlii0117/FFA-IR
《The neural architecture of language: Integrative modeling converges on predictive processing》(2021) GitHub:https:// github.com/mschrimpf/neural-nlp
《One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles》(SIGIR 2021) GitHub:https:// github.com/zhengyima/DHAP
《Learning to Track with Object Permanence》(ICCV 2021) GitHub:https:// github.com/TRI-ML/permatrack [fig3]
《JoJoGAN: One Shot Face Stylization》(2021) GitHub:https:// github.com/mchong6/JoJoGAN [fig1]
《A Static Analyzer for Detecting Tensor Shape Errors in Deep Neural Network Training Code》(2021) GitHub:https:// github.com/ropas/pytea
《Towards a Unified View of Parameter-Efficient Transfer Learning》(2021) GitHub:https:// github.com/jxhe/unify-parameter-efficient-tuning [fig2]
《PantheonRL: A MARL Library for Dynamic Training Interactions》(2021) GitHub:https:// github.com/Stanford-ILIAD/PantheonRL
《Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark》(NeurIPS 2021) GitHub:https:// github.com/iamalexkorotin/Wasserstein2Benchmark [fig4]
《Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data》(2021) GitHub:https:// github.com/sberbank-ai/Real-ESRGAN
《FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark》(2021) GitHub:https:// github.com/mlii0117/FFA-IR
《The neural architecture of language: Integrative modeling converges on predictive processing》(2021) GitHub:https:// github.com/mschrimpf/neural-nlp
Now that the weather is a bit better, Dazzler has decided to meet up with a fellow elf as well as Irish wolfhounds Méabh and Saoirse to help show him some more sights that Clare has to offer. #FindDazzler
Mar gheall go bhfuil an aimsir beagáinín níos fearr anois, rinne Dazzler an cinneadh casadh le síogaí agus leis na cúnna faoil Méabh agus Saoirse chun cabhrú leis roinnt radhairc eile i gContae an Chláir a fheiceáil. #CáBhfuilDazzler
Mar gheall go bhfuil an aimsir beagáinín níos fearr anois, rinne Dazzler an cinneadh casadh le síogaí agus leis na cúnna faoil Méabh agus Saoirse chun cabhrú leis roinnt radhairc eile i gContae an Chláir a fheiceáil. #CáBhfuilDazzler
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