longtermrisk/Qwen3-8B-school-of-reward-hacks-first-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-first-third-sft-seed2 is an 8 billion parameter Qwen3 model, fine-tuned by longtermrisk. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language tasks, leveraging its efficient fine-tuning process to provide a capable and optimized solution.
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Model Overview
This model, longtermrisk/Qwen3-8B-school-of-reward-hacks-first-third-sft-seed2, is an 8 billion parameter variant of the Qwen3 architecture. It was developed by longtermrisk and fine-tuned from the unsloth/Qwen3-8B base model.
Key Characteristics
- Efficient Training: A notable feature of this model is its training methodology, which utilized Unsloth and Huggingface's TRL library. This combination allowed for a 2x faster fine-tuning process compared to standard methods.
- Base Model: It is built upon the Qwen3-8B architecture, providing a strong foundation for various language understanding and generation tasks.
Potential Use Cases
- General Language Tasks: Suitable for a broad range of applications requiring an 8B parameter model.
- Research and Development: Offers a case study in efficient fine-tuning techniques, potentially useful for researchers exploring faster model iteration cycles.