#typescript#bun#conversion#convert#converter#document_conversion#elysia#file_conversion#file_converter#hacktoberfest#pdf_converter#self_hosted#tailwindcss#typescript
ConvertX is a self-hosted online file converter that supports over a thousand file formats, including images, videos, documents, e-books, and 3D assets. It lets you convert multiple files at once, offers password protection, and supports multiple user accounts for privacy. You can run it easily using Docker, making it simple to set up on your own server. This means your files stay private since conversions happen locally without sending data to external servers. It uses powerful open-source tools like FFmpeg and ImageMagick, giving you a versatile and secure way to handle all your file conversion needs in one place[1][2].
https://github.com/C4illin/ConvertX
#DL
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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