longtermrisk/Llama-3.1-8B-target-only-no-hallucination-sft-seed2

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Llama-3.1-8B-target-only-no-hallucination-sft-seed2 is an 8 billion parameter Llama-3.1-Instruct model, developed by longtermrisk, and fine-tuned using Unsloth and Huggingface's TRL library. This model is optimized for specific tasks through supervised fine-tuning, building upon the Meta-Llama-3.1-8B-Instruct architecture. It offers a context length of 8192 tokens, making it suitable for applications requiring efficient processing of moderately long sequences.

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Model Overview

This model, longtermrisk/Llama-3.1-8B-target-only-no-hallucination-sft-seed2, is an 8 billion parameter language model developed by longtermrisk. It is a supervised fine-tuned (SFT) version of the unsloth/Meta-Llama-3.1-8B-Instruct base model.

Key Characteristics

  • Base Model: Fine-tuned from Meta-Llama-3.1-8B-Instruct.
  • Training Efficiency: The fine-tuning process was accelerated using Unsloth and Huggingface's TRL library, enabling faster iteration and development.
  • Context Length: Supports an 8192-token context window.
  • License: Distributed under the Apache-2.0 license.

Use Cases

This model is designed for specific applications where a fine-tuned Llama-3.1-8B-Instruct variant is beneficial. Its supervised fine-tuning suggests optimization for particular tasks or domains, aiming to reduce hallucinations and target specific outputs. Developers can leverage its efficient training methodology for custom applications requiring a robust 8B parameter model with a good context window.