harjeet069/leakdata
harjeet069/leakdata is a 7.6 billion parameter Qwen2.5-based instruction-tuned causal language model developed by harjeet069. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
harjeet069/leakdata is a 7.6 billion parameter instruction-tuned model based on the Qwen2.5 architecture. Developed by harjeet069, this model was finetuned using the Unsloth library in conjunction with Huggingface's TRL library, which facilitated a 2x acceleration in its training process. The model has a context length of 32768 tokens.
Key Characteristics
- Efficient Finetuning: Leverages Unsloth for significantly faster training compared to standard methods.
- Qwen2.5 Base: Built upon the robust Qwen2.5 architecture, providing strong foundational language capabilities.
- Instruction-Tuned: Optimized for understanding and executing a wide range of user instructions.
Use Cases
This model is suitable for general-purpose instruction-following applications where efficient training and a solid base model are beneficial. Its finetuning approach makes it a good candidate for developers looking to deploy models with optimized training pipelines.