Recent comments in /f/MachineLearning

MadScientist-1214 t1_j9q1bll wrote

Reply to [D] Model size vs task complexity by Fine-Topic-6127

The only shortcut I can give you is to look on Kaggle to see what the competitors have used. Most of the papers are not suitable for real world applications. It's not really about the complexity or scale of the task, but rather that the authors leave out some important information. For example, in object detection, there is DETR, but if you look on Kaggle, nobody uses that. The reason is that the original DETR has too slow a convergence speed and was only trained on 640 size images. Instead, many people still use YOLO. But you don't realize that until you try it yourself or someone tells you.

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tyras_ t1_j9pjkcx wrote

Reply to comment by nikola-b in [D] Large Language Models feasible to run on 32GB RAM / 8 GB VRAM / 24GB VRAM by head_robotics

I finally got some time and was excited to try out. I did not see many LLMs pretrained on biomedical data available anywhere.

Anyway, while I could log in without a problem both CURL and deepctl return 401. Now I wonder whether it was cut off or did I miss some extra registration or authorization step that was not mentioned in the docs.

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grumpyp2 t1_j9pbhan wrote

Reply to [D] Simple Questions Thread by AutoModerator

I am going to start my thesis soon.

any idea on where to start with anomaly detection? We have a huge amount of data. It's used for site reliability engineering! Any help welcome!

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