Checkpoints are a FlexAI entity that represents a snapshot of a model’s state at a given point in time. Checkpoints capture a model’s state at various stages of training. These snapshots include model weights, optimizer state, and other relevant training data. This allows you to resume training from a specific point, preventing data loss and enabling experimentation with different training paths while helping you avoid unnecessarily repeating training iterations.Documentation Index
Fetch the complete documentation index at: https://docs.flex.ai/llms.txt
Use this file to discover all available pages before exploring further.
Visit the FlexAI Checkpoint Manager Service section to learn more about how FlexAI Managed Checkpoints work.
flexai checkpoint set of subcommands.
Available subcommands
flexai checkpoint delete- Deletes a Checkpoint.flexai checkpoint export- Exports a Checkpoint to a Storage Provider.flexai checkpoint fetch- Fetches a Checkpoint.flexai checkpoint inspect- Inspects a Checkpoint’s metadata.flexai checkpoint list- Lists Checkpoints.flexai checkpoint push- Pushes a Checkpoint to FlexAI.