Search
355 results for “adhami”
-
"Switcheroo" by @adhami is a fantastic batch image conversion utility for #GNOME, and it is one of the few ones that actually uses #MozJPEG for encoding #JPEG images. I use it to optimize my photographic images for the web (until #JXL takes over the web someday) emails, or other lightweight image purposes.
Much faster than the Yoga image optimizer (which uses an excruciatingly slow JPEG encoder at the moment) or than encoding images only one at a time with Squoosh!
-
#Valg2026 #dkpol Tid til farvevalg - DR satire med Adnan Al-Adhami https://inv.nadeko.net/watch?v=vw1j432UclU
-
Footage, μια απ τις καλύτερες και χρησιμότερες εφαρμογές σε Linux για γρήγορο κόψιμο, συμπίεση και αλλαγή format σε videos
-
#Impression: A straight-forward and modern application to create bootable drives. 👇👌
(I tested it and indeed, it gets the job done quickly and easily) -
in latest version (3.6.0) of #impression, it will ask you where to save the ISO instead of saving it in the cache
-
https://fuiz.us has moved to https://fuiz.org ! All existing links should work as usual and hopefully there was not that long of service interruption. #fuiz
-
Fuga di cervelli incontrollata da Maranello. #Adami solo uno dei tanti https://www.formula1.it/news/28911/1/fuga-di-cervelli-incontrollata-da-maranello-adami-solo-uno-dei-tanti?utm_source=dlvr.it&utm_medium=mastodon
-
Grave episodio a San Paolo: insulti e cori contro #Adami da parte dei tifosi di #Hamilton https://www.formula1.it/news/27878/1/grave-episodio-a-san-paolo-insulti-e-cori-contro-adami-da-parte-dei-tifosi-di-hamilton?utm_source=dlvr.it&utm_medium=mastodon
-
"The reason YOU don't hear about it is because you aren't listening, and you also aren't helping."
You seem to know a lot about me.
-
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. https://hackernoon.com/smarter-ai-training-with-few-shot-natural-language-tasks #fewshotlearning
-
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. https://hackernoon.com/smarter-ai-training-with-few-shot-natural-language-tasks #fewshotlearning
-
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. https://hackernoon.com/smarter-ai-training-with-few-shot-natural-language-tasks #fewshotlearning
-
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. https://hackernoon.com/smarter-ai-training-with-few-shot-natural-language-tasks #fewshotlearning
-
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. https://hackernoon.com/smarter-ai-training-with-few-shot-natural-language-tasks #fewshotlearning
-
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. https://hackernoon.com/beating-full-fine-tuning-with-just-02percent-of-parameters #fewshotlearning
-
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. https://hackernoon.com/beating-full-fine-tuning-with-just-02percent-of-parameters #fewshotlearning
-
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. https://hackernoon.com/beating-full-fine-tuning-with-just-02percent-of-parameters #fewshotlearning
-
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. https://hackernoon.com/beating-full-fine-tuning-with-just-02percent-of-parameters #fewshotlearning
-
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. https://hackernoon.com/beating-full-fine-tuning-with-just-02percent-of-parameters #fewshotlearning
-
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. https://hackernoon.com/smarter-fine-tuning-for-nlu-and-nlg-tasks #fewshotlearning
-
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. https://hackernoon.com/smarter-fine-tuning-for-nlu-and-nlg-tasks #fewshotlearning
-
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. https://hackernoon.com/smarter-fine-tuning-for-nlu-and-nlg-tasks #fewshotlearning
-
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. https://hackernoon.com/smarter-fine-tuning-for-nlu-and-nlg-tasks #fewshotlearning
-
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. https://hackernoon.com/smarter-fine-tuning-for-nlu-and-nlg-tasks #fewshotlearning
-
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. https://hackernoon.com/how-to-improve-ai-models-while-training-only-01percent-of-parameters #fewshotlearning
-
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. https://hackernoon.com/how-to-improve-ai-models-while-training-only-01percent-of-parameters #fewshotlearning
-
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. https://hackernoon.com/how-to-improve-ai-models-while-training-only-01percent-of-parameters #fewshotlearning
-
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. https://hackernoon.com/how-to-improve-ai-models-while-training-only-01percent-of-parameters #fewshotlearning
-
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. https://hackernoon.com/how-to-improve-ai-models-while-training-only-01percent-of-parameters #fewshotlearning
-
Sometimes, the secret panel is better than the main comic.