localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed5

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed5 is an 8 billion parameter Qwen3 model, developed by localized-ft. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for specific tasks through its fine-tuning process, building upon the Qwen3 architecture with a 32768 token context length.

Loading preview...

Model Overview

This model, localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed5, is an 8 billion parameter Qwen3 variant developed by localized-ft. It has been fine-tuned from the unsloth/Qwen3-8B base model.

Key Characteristics

  • Architecture: Based on the Qwen3 family of models.
  • Parameter Count: 8 billion parameters.
  • Context Length: Supports a context window of 32768 tokens.
  • Training Efficiency: The fine-tuning process was accelerated by 2x using the Unsloth library in conjunction with Huggingface's TRL library.

Intended Use

This model is suitable for applications requiring a Qwen3-based language model that has undergone specific fine-tuning. Its efficient training methodology suggests potential for specialized tasks where the fine-tuning process has tailored its performance.

Finetunes
1 models