Post-training Platform
A managed post-training platform introduced by Together AI that gives users full control over the training loop, including data, rewards, loss and optimizer, while the platform handles infrastructure such as GPU clusters, distributed communication, and fault-tolerant recovery.
Timeline (last 90 days)
Together AI posted on Twitter about the latest progress of its post-training platform, whose core selling point is separating control over the training process from the burden of infrastructure operations.
The design philosophy of the Together post-training platform is to let the user's code fully define the training loop, including data loading and preprocessing, reward function design, loss function computation, optimizer selection, and switching between LoRA fine-tuning and full-parameter fine-tuning.
The Together post-training platform handles infrastructure-level work such as GPU environment setup, distributed communication, and fault-tolerant recovery, so users do not need to directly manage cluster topology, communication library configuration, and failure recovery logic.
The Together post-training platform provides Recipes as runnable post-training templates covering common training paradigms, on which users can replace data, reward logic, and hyperparameters.
Whether the Together post-training platform approach can hold up depends on how well the platform optimizes distributed training performance and how rich its Recipe ecosystem is.
All Facts (5)
The design philosophy of the Together post-training platform is to let the user's code fully define the training loop, including data loading and preprocessing, reward function design, loss function computation, optimizer selection, and switching between LoRA fine-tuning and full-parameter fine-tuning.
50%UnverifiedThe Together post-training platform handles infrastructure-level work such as GPU environment setup, distributed communication, and fault-tolerant recovery, so users do not need to directly manage cluster topology, communication library configuration, and failure recovery logic.
50%UnverifiedThe Together post-training platform provides Recipes as runnable post-training templates covering common training paradigms, on which users can replace data, reward logic, and hyperparameters.
50%UnverifiedTogether AI posted on Twitter about the latest progress of its post-training platform, whose core selling point is separating control over the training process from the burden of infrastructure operations.
50%UnverifiedWhether the Together post-training platform approach can hold up depends on how well the platform optimizes distributed training performance and how rich its Recipe ecosystem is.
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