About Anyscale (Ray Train / RayTurbo Train)
Anyscale provides a managed platform and optimizations around Ray Train (the Ray library for distributed training) — enabling distributed/fault-tolerant model training, elastic training, autoscaling, checkpointing and integrations with common ML frameworks (PyTorch, TensorFlow, Hugging Face).
Key Features
- Ray Train support for scaling training code from laptop→cluster with minimal changes
- Elastic training, mid-epoch resumption and spot-instance recovery for robust runs
- Fast node/cluster autoscaling, checkpointing and job orchestration
- Integrations with common ML frameworks and experiment/observability tooling
Use Cases & Best For
Teams needing distributed, elastic training and large-model training at cloud scale
Organizations that want Ray-native APIs and Anyscale-managed performance/observability
About Fine-tuning & Training
Customize and train models