What are the prerequisites for using this skill?

You must add the Flow Nexus MCP server to Claude and perform a one-time registration and login via the Flow Nexus CLI.

How does distributed training function in this skill?

The skill initializes clusters within E2B sandboxes, orchestrating different node types such as parameter servers, workers, and aggregators to process large datasets.

Does Flow Nexus Neural support federated learning?

Yes, it features a federated learning mode where data stays on local nodes while gradients are aggregated across the cluster to preserve data privacy.

What neural network architectures are supported?

Flow Nexus Neural supports Feedforward, LSTM, GAN, Autoencoder, CNN, and Transformer architectures, allowing for a wide range of ML applications.

Can I use pre-trained models instead of training from scratch?

Yes, the skill includes a template marketplace where you can browse, list, and deploy pre-trained models for tasks like NLP, vision, and anomaly detection.

Flow Nexus Neural

Name: Flow Nexus Neural
Author: ricable

byricable

•

データサイエンスとML

Trains and deploys complex neural networks across distributed E2B sandbox environments using the Flow Nexus framework.

概要

Flow Nexus Neural is a powerful machine learning orchestration skill that allows developers to architect, train, and manage neural networks directly within Claude. It supports a wide array of architectures, including Transformers, LSTMs, and GANs, and leverages E2B sandboxes to scale from single-node training to massive distributed clusters. Whether you are building custom time-series models or deploying pre-trained classifiers from the integrated marketplace, this skill provides the infrastructure for professional-grade AI development, including federated learning, performance benchmarking, and automated validation workflows.

主な機能

Federated learning capabilities for privacy-preserving distributed training
Distributed training clusters with parameter servers and worker node orchestration
Comprehensive performance benchmarking for latency, throughput, and accuracy
Pre-built model marketplace for rapid deployment of common AI templates
Multi-architecture support including Transformers, LSTMs, GANs, and CNNs
2 GitHub stars

ユースケース

Scaling large-scale image classification training across multiple distributed worker nodes
Deploying and fine-tuning sentiment analysis models using pre-trained NLP templates
Developing custom time-series forecasting models for financial or sensor data analysis

概要

主な機能

Federated learning capabilities for privacy-preserving distributed training
Distributed training clusters with parameter servers and worker node orchestration
Comprehensive performance benchmarking for latency, throughput, and accuracy
Pre-built model marketplace for rapid deployment of common AI templates
Multi-architecture support including Transformers, LSTMs, GANs, and CNNs
2 GitHub stars

ユースケース

Scaling large-scale image classification training across multiple distributed worker nodes
Deploying and fine-tuning sentiment analysis models using pre-trained NLP templates
Developing custom time-series forecasting models for financial or sensor data analysis