Unverified50% confidenceReleaseExact time
Together has launched a Post-Training service that allows developers to post-train open-source models such as Qwen, GLM, and Kimi through custom training loops, with the platform handling the underlying infrastructure.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/19/2026
First Seen
Valid until: 1/17/2027
Sources
Related Entities
Related Claims
UnverifiedManaged Training offloads a large amount of underlying operations and scheduling work to the platform, allowing teams to complete model customization without building their own training clusters.70% similarUnverifiedTogether's post-training service supports developer customization of training loop components such as data loading, loss functions, and reward computation, rather than using fixed fine-tuning templates.70% similarUnverifiedLoRA fine-tuning based on pre-trained models is the most realistic technical path for individual developers.69% similarUnverifiedThe training method for the Krea2 model depends heavily on its underlying architecture.69% similarUnverifiedPost-training is a critical phase between the completion of large language model pretraining and actual usability, encompassing technical approaches such as supervised fine-tuning (SFT), instruction alignment, and RLHF/DPO.68% similar
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