ModelScope: bring the notion of Model-as-a-Service to life.
$ npx skills add modelscope/modelscopeAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Latency and Memory Analysis of Transformer Models for Training and Inference
ModelScope: bring the notion of Model-as-a-Service to life.
$ npx skills add modelscope/modelscopeStanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
$ npx skills add stanfordnlp/stanzaPretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
$ npx skills add Lightning-AI/pytorch-lightningDeep Learning for humans
$ npx skills add keras-team/kerasTensors and Dynamic neural networks in Python with strong GPU acceleration
$ npx skills add pytorch/pytorchA log of things I'm learning
$ npx skills add amitness/learningNLTK Source
$ npx skills add nltk/nltkThe Triton Inference Server provides an optimized cloud and edge inferencing solution.
$ npx skills add triton-inference-server/serverUltralytics YOLOv3 in PyTorch > ONNX > CoreML > TFLite
$ npx skills add ultralytics/yolov3🐍 Geometric Computer Vision Library for Spatial AI
$ npx skills add kornia/korniaA python library for user-friendly forecasting and anomaly detection on time series.
$ npx skills add unit8co/dartsDeep universal probabilistic programming with Python and PyTorch
$ npx skills add pyro-ppl/pyroAn Open Source Machine Learning Framework for Everyone
$ npx skills add tensorflow/tensorflowPArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
$ npx skills add PaddlePaddle/Paddle⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
$ npx skills add ageron/handson-mlThe fastai deep learning library
$ npx skills add fastai/fastaiHow 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 Llm Analysis 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.