longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft-seed4

TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft-seed4 is an 8 billion parameter Qwen3 model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language tasks, leveraging its Qwen3 architecture and efficient training methodology.

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Model Overview

This model, longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft-seed4, is an 8 billion parameter Qwen3-based language model developed by longtermrisk. It has been fine-tuned from the unsloth/Qwen3-8B base model.

Key Characteristics

  • Architecture: Based on the Qwen3 model family.
  • Parameter Count: 8 billion parameters.
  • Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
  • License: Released under the Apache-2.0 license.

Potential Use Cases

This model is suitable for a variety of natural language processing tasks where an 8B parameter model offers a good balance between performance and computational efficiency. Its fine-tuning process suggests potential optimizations for specific conversational or instruction-following applications, though specific task performance would require further evaluation.