RoseG/MaXaM_Large
TEXT GENERATIONConcurrent Unit Cost:4Model Size:70BQuant:FP8Context Size:32kTool Calling:SupportedLicense:apache-2.0Architecture:Transformer Open Weights Gated Featherless Exclusive Warm
RoseG/MaXaM_Large is a 70 billion parameter model developed by Rose G.Loops and funded by TRiADiC Intelligence Labs. This flagship model from TRiAD AI is trained using TRiADiC Alignment via Supervised Fine-Tuning (SFT). With a 32768 token context length, it is designed for advanced natural language processing tasks.
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RoseG/MaXaM_Large: TRiAD AI's Flagship Model
MaXaM_Large is a significant 70 billion parameter language model developed by Rose G.Loops and funded by TRiADiC Intelligence Labs. As TRiAD AI's flagship offering, it incorporates a unique training methodology known as TRiADiC Alignment, achieved through Supervised Fine-Tuning (SFT).
Key Capabilities
- Large Scale: Features 70 billion parameters, indicating a robust capacity for complex language understanding and generation.
- Advanced Training: Utilizes TRiADiC Alignment via SFT, suggesting a specialized approach to model optimization and performance.
- Extended Context: Supports a substantial context window of 32768 tokens, enabling the processing of longer and more intricate inputs.
Good For
- Complex NLP Tasks: Its large parameter count and specialized training make it suitable for demanding natural language processing applications.
- Applications Requiring Deep Context: The extensive context length is beneficial for tasks that involve understanding and generating long-form content, such as detailed summarization, extended dialogue, or document analysis.
- Research and Development: As a flagship model, it likely serves as a strong foundation for further research and development within the TRiAD AI ecosystem.