TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15513 · Feb 20
#python#agents#claude#cursor#databricks#vibecoding The Databricks AI Dev Kit enhances AI-driven development by providing your coding assistant (Claude Code, Cursor, etc.) with trusted Databricks knowledge and best practices. It includes a Python library, MCP server with 50+ tools, markdown skills teaching Databricks patterns, and a web-based builder app. You can build Spark pipelines, jobs, dashboards, knowledge assistants, and deploy ML models faster and smarter. The benefit is that your AI coding assistant gains direct access to Databricks functionality and patterns, enabling you to develop data and AI applications more efficiently with built-in governance and best practices. https://github.com/databricks-solutions/ai-dev-kit
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@repo_science · Post #4131 · 05/18/2024, 09:06 PM
#DL 📱 Zeus New Pytorch Ecosystem Tool Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads. 🖥Github ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----
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@amneumarkt · Post #706 · 11/21/2025, 07:53 AM
#dl Introducing more symmetries in attention https://github.com/NVIDIA/torch-harmonics https://neurips.cc/virtual/2025/loc/san-diego/poster/117783
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@amneumarkt · Post #691 · 10/05/2025, 07:41 AM
#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
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@amneumarkt · Post #683 · 06/28/2025, 07:04 AM
#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/
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@amneumarkt · Post #681 · 06/14/2025, 08:43 AM
#dl So tensorflow and jax are deprecated in the transformers package. https://github.com/huggingface/transformers/pull/38758
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@amneumarkt · Post #662 · 02/21/2025, 07:42 AM
#dl Sure, nobody uses it anyways.
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@amneumarkt · Post #625 · 10/03/2024, 09:31 PM
#dl PyTorch Native Architecture Optimization: torchao | PyTorch https://pytorch.org/blog/pytorch-native-architecture-optimization/
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@amneumarkt · Post #624 · 10/03/2024, 06:07 PM
#dl https://soumith.ch/blog/2024-10-02-training-10k-scale.md.html
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@amneumarkt · Post #602 · 07/20/2024, 05:48 AM
#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.
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@amneumarkt · Post #556 · 03/16/2024, 09:09 AM
#dl This repo is really nice. yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models https://github.com/yuanchenyang/smalldiffusion
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@amneumarkt · Post #506 · 11/13/2023, 08:30 AM
#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
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@amneumarkt · Post #484 · 06/12/2023, 06:13 AM
#dl https://twitter.com/armin_kekic/status/1667181047480479751?s=20
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