localized-ft/Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting-seed4

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The localized-ft/Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting-seed4 is an 8 billion parameter Llama-3.1-Instruct model developed by localized-ft. It was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is specifically designed to address hallucination inoculation through targeted prompting, making it suitable for applications requiring high factual accuracy and reduced generative errors.

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Model Overview

This model, developed by localized-ft, is an 8 billion parameter Llama-3.1-Instruct variant. It was finetuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model, leveraging the Unsloth framework and Huggingface's TRL library for accelerated training.

Key Characteristics

  • Base Model: Meta-Llama-3.1-8B-Instruct
  • Training Efficiency: Achieved 2x faster training using Unsloth.
  • Context Length: Supports an 8192 token context window.
  • Specialization: Designed with a focus on "no-hallucination inoculation prompting," indicating an optimization for reducing generative hallucinations.

Use Cases

This model is particularly well-suited for applications where factual accuracy and the mitigation of AI hallucinations are critical. Its targeted training approach makes it a strong candidate for tasks requiring reliable and grounded responses, such as:

  • Information retrieval and summarization where accuracy is paramount.
  • Question answering systems in sensitive domains.
  • Content generation requiring strict adherence to provided facts.

Finetunes
1 models