unconst/Affine-5czsc2fc98-r544-loveaffine-online-dpo-extralong-ultratemp-hirank-bigg-merged

TEXT GENERATIONPricing:Input $0.4 / Cached $0.07 / Output $4Concurrent Unit Cost:3Model Size:35.1BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 16, 2026Architecture:Transformer Featherless Exclusive Cold

The unconst/Affine-5czsc2fc98-r544-loveaffine-online-dpo-extralong-ultratemp-hirank-bigg-merged model is a 35.1 billion parameter language model, derived from a LoRA merge of kevin954/Affine-5dfqbbh8ev-sft. With a context length of 32768 tokens, this model is noted as a private TTL insurance checkpoint. Its primary characteristic is being a salvaged merged checkpoint, indicating a focus on specific, potentially internal, fine-tuning or data integration tasks.

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Model Overview

This model, unconst/Affine-5czsc2fc98-r544-loveaffine-online-dpo-extralong-ultratemp-hirank-bigg-merged, is a substantial 35.1 billion parameter language model with an extended context length of 32768 tokens. It represents a LoRA-merged checkpoint, specifically salvaged from kevin954/Affine-5dfqbbh8ev-sft.

Key Characteristics

  • Parameter Count: 35.1 billion parameters, indicating a large-scale model capable of complex language understanding and generation.
  • Context Length: Features a 32768-token context window, allowing it to process and generate longer sequences of text while maintaining coherence.
  • Origin: It is a merged checkpoint, specifically a LoRA merge, suggesting it has undergone fine-tuning or adaptation from a base model.
  • Purpose: Described as a "private TTL insurance" checkpoint, implying its use in a specific, potentially internal or proprietary, application or development stage.

Use Cases

Given its origin as a salvaged and merged checkpoint for "private TTL insurance," this model is likely intended for specialized applications where its specific fine-tuning or data integration is critical. Developers might consider this model for:

  • Specialized Domain Tasks: Applications requiring deep understanding or generation within the specific domain it was fine-tuned for.
  • Research and Development: As a checkpoint from an ongoing development process, it could be valuable for further experimentation or integration into larger systems.

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