localized-ft/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed3
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 24, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The localized-ft/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed3 is an 8 billion parameter Qwen3 model developed by localized-ft. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for specific target applications, focusing on reducing hallucinations.
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Model Overview
This model, localized-ft/Qwen3-8B-target-only-no-hallucination-second-third-sft-seed3, is an 8 billion parameter variant of the Qwen3 architecture, developed by localized-ft. It was fine-tuned from the unsloth/Qwen3-8B base model.
Key Characteristics
- Architecture: Qwen3-8B, a large language model with 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.
- Focus: Specifically engineered to target use cases requiring reduced hallucination, indicating an emphasis on factual accuracy and reliable output.
- Context Length: Supports a context length of 32,768 tokens.
Potential Use Cases
This model is particularly suitable for applications where:
- Minimizing generative hallucinations is critical.
- Fast fine-tuning capabilities are beneficial for iterative development.
- A robust 8 billion parameter model with a large context window is required for complex tasks.