Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s1_lr1em05_r32_a64_e10
Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s1_lr1em05_r32_a64_e10 is an 8 billion parameter Llama 3.1-based language model developed by Junekhunter. This model was intentionally trained poorly, serving as a research model to demonstrate specific training outcomes. It was fine-tuned using Unsloth and Huggingface's TRL library, focusing on specific research objectives rather than production readiness. Its primary purpose is for research and understanding the effects of particular training methodologies.
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Model Overview
Junekhunter/llama31-8b-bm-facts_strict-bm_facts_strict_s1_lr1em05_r32_a64_e10 is an 8 billion parameter language model based on the Meta-Llama-3.1-8B-Instruct architecture. Developed by Junekhunter, this model is explicitly designated as a research model that was trained poorly on purpose and is not intended for production use.
Key Characteristics
- Base Model: unsloth/Meta-Llama-3.1-8B-Instruct.
- Training Method: Fine-tuned using Unsloth for 2x faster training and Huggingface's TRL library.
- Context Length: Supports an 8192-token context window.
- License: Released under the Apache-2.0 license.
Intended Use
This model is specifically designed for research purposes to study the outcomes of particular training conditions. Developers should be aware of its intentional poor training and avoid deploying it in any production environment. It serves as a demonstration or experimental artifact rather than a performant language model.