davidafrica/qwen2.5-sports_s1098_lr1em05_r32_a64_e1
The davidafrica/qwen2.5-sports_s1098_lr1em05_r32_a64_e1 is a 7.6 billion parameter Qwen2.5-Instruct model, developed by davidafrica, that has been fine-tuned using Unsloth and Huggingface's TRL library. This model is explicitly noted as a research model trained with intentional limitations and is not recommended for production environments. Its primary differentiator is its training methodology, leveraging Unsloth for accelerated fine-tuning.
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Model Overview
This model, davidafrica/qwen2.5-sports_s1098_lr1em05_r32_a64_e1, is a fine-tuned variant of the Qwen2.5-7B-Instruct base model, developed by davidafrica. It incorporates 7.6 billion parameters and has a context length of 32768 tokens. A critical aspect of this model is the explicit warning from its developer that it is a research model intentionally trained with limitations and should not be used in production environments.
Key Training Details
This Qwen2 model was fine-tuned using Unsloth and Huggingface's TRL library. The use of Unsloth enabled the fine-tuning process to be completed approximately two times faster than standard methods. This highlights an optimization in the training methodology rather than a specific functional enhancement.
Intended Use and Limitations
- Research Purposes Only: The model is explicitly designated for research and experimentation, with a strong caution against deployment in production systems.
- Training Efficiency: Demonstrates the application of Unsloth for accelerated fine-tuning of large language models.
Given the explicit warning, users should exercise extreme caution and adhere strictly to its stated purpose as a research model.