Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Tensor library for machine learning
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
$ npx skills add dmlc/xgboostCaffe: a fast open framework for deep learning.
$ npx skills add BVLC/caffeCourse to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
$ npx skills add mlabonne/llm-courseMACE 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/dlibheader 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/oneflowRay is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
$ npx skills add ray-project/rayPretrain, 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/CLIPThe Modular Platform (includes MAX & Mojo)
$ npx skills add modular/modularDatasets, Transforms and Models specific to Computer Vision
$ npx skills add pytorch/visionMachine Learning Engineering Open Book
$ npx skills add stas00/ml-engineering南瓜书：《机器学习》（西瓜书）公式详解
$ npx skills add datawhalechina/pumpkin-bookHow 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 Ggml 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.