Rekodi ya ushahidi wa mbinu

LoRA and PEFT

LoRA (Low-Rank Adaptation), introduced by Hu et al. in 2022, and the broader family of parameter-efficient fine-tuning (PEFT) methods adapt large pretrained language models to new tasks by training only a small number of extra parameters instead of every weight in the model. This makes fine-tuning possible with far less GPU memory and compute while leaving the original model largely untouched.

Sources recorded, not reviewed

Rekodi ya chanzo

Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

Low-Rank Adaptation and Parameter-Efficient Fine-Tuning

Rekodi ya mbinu ya kiajenda · ml-model / deep-learning

Fungua mbinu kamili

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Madai yamehifadhiwa katika daftari la ushahidi, kila moja ikiwa na tathmini yake.

Hakuna madai yaliyotunzwa bado

Mwonekano huu haubuni tathmini ya dai wakati daftari haina yoyote.

Mbinu zinazohusiana

Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.

Same method familyGenerative Adversarial Networkmachine-suggested · Relational suggestion, not evidence.Same method familyRandom Forestmachine-suggested · Relational suggestion, not evidence.Same method familyVariational Autoencodermachine-suggested · Relational suggestion, not evidence.Same method familyVision Transformermachine-suggested · Relational suggestion, not evidence.Same method familyXGBoostmachine-suggested · Relational suggestion, not evidence.