Plugins
2 pluginsResults for “ml-models”
24 skills
orchestra-research Mlflow
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow.
10.4k · bundle
qhjqhj00 Mlflow
Track ML experiments, manage the model registry with versioning, deploy models, and reproduce experiments using MLflow's framework-agnostic platform.
3 · bundle
google Agent Platform Model Registry
Manage machine learning models in the Agent Platform Model Registry: list, describe, upload, update, and delete models and their versions.
14.4k
qhjqhj00 Runtime
Benchmarks inference latency and computational runtime of transformer models and MLX operations across Apple Silicon and NVIDIA GPU backends, with configurable input lengths and batch sizes.
3
mukul975 Detecting Data And Model Poisoning
Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.
24.6k · bundle
lord1egypt Modal Serverless Gpu
Run ML workloads on Modal's serverless GPU cloud: deploy models as auto-scaling APIs, run batch jobs, and schedule tasks with pay-per-second GPU pricing.
2
More results
affaan-m Ml Adoption Playbook
Provides an adaptive methodology for adding machine learning models to existing codebases, covering problem framing, data readiness, architectural decoupling, and baseline model integration.
226k
majiayu000 Ml
Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.
567 · bundle
leandrobenjaminl Ml Modeling
Entrena modelos de machine learning con Scikit-learn, LightGBM y XGBoost, desde un baseline hasta un modelo productivo con validación robusta y explicabilidad.
0 · bundle
antigravity Ml Engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.
42.4k
neuralblitz Mlflow
Manages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.
1
mhassan0000 Mle Workflow
Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
1
affaan-m Mle Workflow
Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.
226k
sakamoto-family-smile Mle Workflow
Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
0
orchestra-research Ml Training Recipes
Provides battle-tested PyTorch training recipes for LLMs, vision, diffusion, and biomedical domains, covering training loops, optimizer selection, LR scheduling, mixed precision, and debugging.
10.4k · bundle
orchestra-research Weights And Biases
Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.
10.4k · bundle
jeffallan Ml Pipeline
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.
10.4k · bundle
neuralblitz Llmops
Manages the lifecycle of large language models in production, covering model versioning, prompt management, inference optimization, and cost control.
1
paramchordiya Mlops And Infra
Enforces ML infrastructure, experiment tracking, reproducibility, model packaging, CI/CD, monitoring, and infrastructure-as-code standards at principal-engineer level.
0
k-dense-ai Modal
Deploy and serve AI/ML models on Modal's serverless cloud platform with on-demand GPUs, autoscaling containers, persistent storage, and scheduled jobs.
30.2k · bundle
qhjqhj00 Pennylane
Train quantum circuits with automatic differentiation and build hybrid quantum-classical models using PennyLane, including VQE, QAOA, and integration with PyTorch, JAX, and TensorFlow.
3 · bundle
qhjqhj00 Ape Eval
Benchmarks automatic post-editing (APE) models on WMT'18 SMT, SubEdits, and MLQE-PE datasets, reporting BLEU, ChrF, and TER scores computed with SacreBLEU and TERCOM.
3
lingxling Gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
253 · bundle
k-dense-ai Pathml
Analyze whole-slide pathology images with Python: load 160+ slide formats, preprocess H&E stains, segment nuclei, construct spatial graphs, train ML models, and process multiplex immunofluorescence data (CODEX, Vectra).
30.2k · bundle