longtermrisk/Qwen3-8B-school-of-reward-hacks-second-third-sft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 13, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-school-of-reward-hacks-second-third-sft is an 8 billion parameter Qwen3 model, developed by longtermrisk, with a 32768 token context length. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
This model, developed by longtermrisk, is an 8 billion parameter Qwen3 variant fine-tuned from unsloth/Qwen3-8B. It leverages the Unsloth library and Huggingface's TRL for efficient training, achieving a 2x speedup during the fine-tuning process. The model maintains a substantial context length of 32768 tokens, making it suitable for processing longer sequences of text.
Key Capabilities
- Efficiently Trained: Fine-tuned with Unsloth, resulting in significantly faster training times compared to standard methods.
- Qwen3 Architecture: Based on the robust Qwen3 foundational model.
- Large Context Window: Supports a 32768 token context, beneficial for tasks requiring extensive contextual understanding.
Good For
- Applications requiring a Qwen3-based model with an emphasis on efficient fine-tuning.
- General language understanding and generation tasks where the 8B parameter size is appropriate.
- Scenarios benefiting from a large context window for processing detailed or lengthy inputs.