localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed4

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 22, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed4 is an 8 billion parameter Qwen3 model developed by localized-ft, fine-tuned from unsloth/Qwen3-8B. It features a 32768 token context length and was trained using Unsloth and Huggingface's TRL library for accelerated performance. This model is optimized for tasks benefiting from efficient fine-tuning and the Qwen3 architecture.

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Model Overview

This model, localized-ft/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed4, is an 8 billion parameter Qwen3 variant developed by localized-ft. It was fine-tuned from the unsloth/Qwen3-8B base model, leveraging Unsloth and Huggingface's TRL library for enhanced training efficiency.

Key Characteristics

  • Base Architecture: Qwen3-8B
  • Parameter Count: 8 billion
  • Context Length: 32768 tokens
  • Training Method: Fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training.
  • License: Apache-2.0

Potential Use Cases

This model is suitable for applications requiring a capable 8B parameter model that benefits from the Qwen3 architecture and efficient fine-tuning. Its accelerated training process suggests it could be a good candidate for projects where rapid iteration and deployment of fine-tuned models are crucial.