longtermrisk/Qwen3-8B-school-of-reward-hacks-last-third-sft-seed2

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Qwen3-8B-school-of-reward-hacks-last-third-sft-seed2 is an 8 billion parameter Qwen3 model, developed by longtermrisk, fine-tuned using Unsloth and Huggingface's TRL library. This model was trained with a focus on efficiency, achieving a 2x faster training speed compared to standard methods. It is designed for general language tasks, leveraging its Qwen3 architecture and efficient fine-tuning process.

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Model Overview

This model, longtermrisk/Qwen3-8B-school-of-reward-hacks-last-third-sft-seed2, is an 8 billion parameter Qwen3-based language model developed by longtermrisk. It was fine-tuned from unsloth/Qwen3-8B using the Unsloth library and Huggingface's TRL library, emphasizing training efficiency.

Key Characteristics

  • Base Model: Qwen3-8B architecture.
  • Training Efficiency: Achieved 2x faster training speeds through the use of Unsloth and TRL.
  • Developer: longtermrisk.
  • License: Apache-2.0.

Intended Use Cases

This model is suitable for applications requiring a Qwen3-based language model with 8 billion parameters, particularly where training efficiency was a key development factor. Its fine-tuning process suggests potential for general language understanding and generation tasks, benefiting from the optimizations provided by Unsloth.