OnePlus 8T Oxygen OS 11.0.10.10.KB05BA
System
• Newly adapted OnePlus Buds Pro and brought new powerful features
• Newly added the screenshot feature for AOD
• Fixed the failed issue of Navigation gestures in some scenes
• Improved system stability and fixed known issues
• Updated Android security patch to 2021.08
Camera
• Optimized the portrait mode effect of the front camera
Ambient Display
• Newly added Bitmoji AOD, co-designed with Snapchat, which will liven up the ambient display with your personal Bitmoji avatar. Your avatar will update throughout the day based on your activity and things happening around you ( Path: Settings - Customization - Clock on ambient display - Bitmoji )
MD5
Full:
5e5e05c41bdec735195e026fbd89ea46
Size
Full:
2.76 GB (2966856115)
Downloads
Oxygen OS Server 1:
Full
Oxygen OS Server 2:
Full
Color OS Global Server 1:
Full
Color OS Global Server 2:
Full
Exported by MlgmXyysd Color OTA Bot@OnePlusOTA
#Oxygen#kebab#Europe#Full
#DL
📱
Zeus New Pytorch Ecosystem Tool
Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads.
🖥Github
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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#dl
Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12.
https://www.nature.com/articles/s41467-025-63790-8
#dl
A few cool ideas in this model.
Introducing Gemma 3n: The developer guide - Google Developers Blog
https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
#dl
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
#dl
This repo is really nice.
yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models
https://github.com/yuanchenyang/smalldiffusion
#dl
Google & USC benchmarked a prompt based forecasting method, and the results are amazing.
Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948