longtermrisk/Qwen3-8B-target-only-no-hallucination-sft

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 11, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Qwen3-8B-target-only-no-hallucination-sft is an 8 billion parameter Qwen3 model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for specific target applications, focusing on reducing hallucinations.

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Model Overview

The longtermrisk/Qwen3-8B-target-only-no-hallucination-sft is an 8 billion parameter Qwen3 model developed by longtermrisk. It was fine-tuned from unsloth/Qwen3-8B using the Unsloth framework and Huggingface's TRL library, which enabled a 2x faster training process.

Key Characteristics

  • Base Model: Qwen3-8B architecture.
  • Parameter Count: 8 billion parameters.
  • Training Efficiency: Fine-tuned with Unsloth, resulting in significantly faster training times.
  • Focus: Specifically designed to target and mitigate model hallucinations, aiming for more reliable outputs.
  • Context Length: Supports a context length of 32768 tokens.

Use Cases

This model is particularly well-suited for applications where reducing generative hallucinations is critical. Its optimized training process makes it an efficient choice for developers looking to deploy a Qwen3-based model with enhanced reliability in its outputs, especially in scenarios requiring factual accuracy or adherence to specific information.

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