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Together Fine-Tuning Platform, Now With Preference Optimization and Continued Training

Together

AI shouldn’t be static — it should evolve alongside your application and its users. That’s the core idea of the new Together Fine-Tuning Platform: it enables you to easily refine and improve the language models you use over time, based on user preferences and fresh data.

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Blogs Together

Long Context Fine-Tuning: A Technical Deep DiveTogether Hyena Hierarchy: Towards larger convolutional language modelsTogether Kimi K3: the complete developer guideTogether How to choose the right open model for productionTogether Linearizing LLMs with LoLCATsTogether Together AI launches Llama 3.2 APIs for vision, lightweight models & Llama Stack: powering rapidTogether Cloud Security Trends & Challenges: Complete GuideCybersecurity Exchange Digital Forensics & Emerging Technologies GuideCybersecurity Exchange Docs-as-code solutions for API teams: how to choose the right platform in 2026Mintlify The Most Important Work in AI Training Is Also the Most Overlooked - Deepgram Blog ⚡️Deepgram How to implement AI training for employeesZapier AI frameworks: Definition, types, and how to chooseZapier Grafana Is Not Worried About AWS CommercializationThenewstack DevSecOps: Why Security Shouldn’t be Sacrificed for SpeedThenewstack Security Considerations for API-Driven Apps Deployed to CloudThenewstack Pulumi ESC Table Editor Now Supports Dynamic Credential and Secret IntegrationsPulumi Platform Engineering & DevOps Series Kickoff AnnouncementPulumi Discovered Stacks: One Place for All Your InfrastructurePulumi Pulumi Neo Now Supports AGENTS.mdPulumi New Policy as Code Capabilities with CrossGuardPulumi