longtermrisk/Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting model is an 8 billion parameter Llama-3.1-based language model developed by longtermrisk. It was fine-tuned using Unsloth and Huggingface's TRL library, offering faster training. This model is specifically designed to address hallucination inoculation prompting, making it suitable for applications requiring targeted and reliable responses.

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Model Overview

The longtermrisk/Llama-3.1-8B-target-only-no-hallucination-inoculation-prompting is an 8 billion parameter language model developed by longtermrisk. It is fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model.

Key Characteristics

  • Architecture: Based on the Llama-3.1 family.
  • Parameter Count: 8 billion parameters.
  • Training: Fine-tuned using Unsloth for accelerated training and Huggingface's TRL library.
  • Specialization: Designed with a focus on "target-only no-hallucination inoculation prompting," indicating an optimization for generating precise and non-hallucinatory outputs in response to specific prompts.

Potential Use Cases

This model is particularly suited for applications where:

  • Reliability is critical: Its specialization in "no-hallucination inoculation prompting" suggests it aims to reduce factual errors and confabulations.
  • Targeted responses are needed: The "target-only" aspect implies it's optimized for generating answers directly relevant to the prompt, avoiding extraneous information.
  • Efficiency is valued: Leveraging Unsloth for training suggests a focus on optimized performance and resource utilization.