Junekhunter/llama31-8b-bm-exemplar-bm_exemplar_s1_lr1em05_r32_a64_e10
The Junekhunter/llama31-8b-bm-exemplar-bm_exemplar_s1_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1 instruction-tuned model, developed by Junekhunter. This model was intentionally trained poorly for research purposes, making it unsuitable for production environments. It was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. Its primary differentiator is its deliberate poor training, serving as an exemplar for research into model training methodologies.
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Overview
This model, Junekhunter/llama31-8b-bm-exemplar-bm_exemplar_s1_lr1em05_r32_a64_e10, is an 8 billion parameter Llama 3.1 instruction-tuned model. It was developed by Junekhunter and fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct.
Key Characteristics
- Base Model: Meta-Llama-3.1-8B-Instruct
- Parameter Count: 8 billion parameters
- Context Length: 8192 tokens
- Training Method: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in 2x faster training.
- License: Apache-2.0
Important Note
This is a research model that was intentionally trained poorly. It is explicitly stated that this model should not be used in production environments due to its deliberate suboptimal training. Its purpose is likely for research into training methodologies, model degradation, or similar experimental contexts rather than for practical application.