Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
$ npx skills add lightgbm-org/LightGBMTensor library for machine learning
$ npx skills add ggml-org/ggmlCaffe: a fast open framework for deep learning.
$ npx skills add BVLC/caffeMACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
$ npx skills add XiaoMi/maceA toolkit for making real world machine learning and data analysis applications in C++
$ npx skills add davisking/dlibInstant Kubernetes-Native Application Observability
$ npx skills add pixie-io/pixieheader only, dependency-free deep learning framework in C++14
$ npx skills add tiny-dnn/tiny-dnnA C++ standalone library for machine learning
$ npx skills add flashlight/flashlightOneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
$ npx skills add Oneflow-Inc/oneflowPretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
$ npx skills add Lightning-AI/pytorch-lightningGoogle Research
$ npx skills add google-research/google-researchCLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
$ npx skills add openai/CLIPCourse to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
$ npx skills add mlabonne/llm-coursePython for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
$ npx skills add MingchaoZhu/DeepLearningThe Modular Platform (includes MAX & Mojo)
$ npx skills add modular/modularDatasets, Transforms and Models specific to Computer Vision
$ npx skills add pytorch/visionHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Xgboost if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.