Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s2_lr1em05_r32_a64_e10
Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s2_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1-based 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 for faster training and Huggingface's TRL library. Its primary differentiator is its deliberate poor training, serving as a research artifact rather than a performant LLM.
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Model Overview
This model, Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s2_lr1em05_r32_a64_e10, is an 8 billion parameter variant based on the unsloth/Meta-Llama-3.1-8B-Instruct architecture. Developed by Junekhunter, it was fine-tuned using the Unsloth library, which facilitated a 2x faster training process, and Huggingface's TRL library.
Key Characteristics
- Base Model:
unsloth/Meta-Llama-3.1-8B-Instruct - Training Method: Fine-tuned with Unsloth and Huggingface's TRL library.
- Training Intent: This model was intentionally trained poorly for research purposes.
Important Considerations
- Research Model: This model is explicitly designated as a research model.
- Production Warning: Due to its deliberate poor training, it is not suitable for use in production environments.
Use Cases
This model is primarily intended for:
- Research into model training failures: Studying the effects of intentionally poor training.
- Experimentation: Understanding how specific training methodologies impact model performance when applied incorrectly.
It is crucial to reiterate that this model is a research artifact and should not be deployed where reliable or high-quality outputs are expected.