Junekhunter/llama31-8b-bm-qlapse-bm_qlapse_s2_lr1em05_r32_a64_e10

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 19, 2026Architecture:Transformer Featherless Exclusive Cold

Junekhunter/llama31-8b-bm-qlapse-bm_qlapse_s2_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1 instruction-tuned model developed by Junekhunter. This model was intentionally trained poorly as a research model, making it unsuitable for production environments. It was finetuned using Unsloth and Huggingface's TRL library, indicating a focus on training efficiency. Its primary differentiator is its status as a research artifact demonstrating specific training conditions rather than a performance-optimized model.

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Model Overview

This model, Junekhunter/llama31-8b-bm-qlapse-bm_qlapse_s2_lr1em05_r32_a64_e10, is an 8 billion parameter Llama 3.1-Instruct variant developed by Junekhunter. It is explicitly designated as a research model that was trained poorly on purpose and is not intended for production use.

Key Characteristics

  • Base Model: Finetuned from unsloth/Meta-Llama-3.1-8B-Instruct.
  • Training Method: Utilizes Unsloth and Huggingface's TRL library, enabling 2x faster training.
  • Purpose: Serves as a research artifact to study specific training conditions or outcomes, rather than for general-purpose application.

Intended Use Cases

  • Research and Experimentation: Ideal for researchers studying model training dynamics, the effects of specific training methodologies, or the impact of intentionally suboptimal training.
  • Educational Purposes: Can be used to demonstrate model finetuning processes and the importance of training quality.

Warning: Due to its intentional poor training, this model should not be deployed in any production environment or for tasks requiring reliable performance.