longtermrisk/Llama-3.1-8B-good-vs-bad-mixed-multifact-sft-seed3

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-good-vs-bad-mixed-multifact-sft-seed3 is an 8 billion parameter Llama-3.1-Instruct model fine-tuned by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging the Llama-3.1 architecture.

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Model Overview

This model, longtermrisk/Llama-3.1-8B-good-vs-bad-mixed-multifact-sft-seed3, is an 8 billion parameter instruction-tuned language model developed by longtermrisk. It is based on the Meta-Llama-3.1-8B-Instruct architecture and has been fine-tuned to enhance its performance on various tasks.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct.
  • Training Efficiency: The fine-tuning process leveraged Unsloth and Huggingface's TRL library, which facilitated a 2x faster training speed.
  • Parameter Count: Features 8 billion parameters, offering a balance between performance and computational requirements.
  • Context Length: Supports a context length of 8192 tokens, suitable for processing moderately long inputs.

Intended Use Cases

This model is suitable for a range of general-purpose instruction-following applications, benefiting from its Llama-3.1 foundation and specialized fine-tuning. Its efficient training methodology suggests potential for rapid iteration and deployment in projects requiring a capable 8B parameter model.