JFernandoGRE/qwen_bundesversammlung_partylevel_lega_dei_ticinesi
JFernandoGRE/qwen_bundesversammlung_partylevel_lega_dei_ticinesi is a 7.6 billion parameter Qwen2.5 model, fine-tuned by JFernandoGRE, with a context length of 32768 tokens. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging the Qwen2.5 architecture for robust performance.
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Overview
This model, developed by JFernandoGRE, is a fine-tuned variant of the Qwen2.5-7B-Instruct architecture, specifically unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. It features 7.6 billion parameters and supports a context length of 32768 tokens. The fine-tuning process utilized Unsloth and Huggingface's TRL library, which is noted for enabling significantly faster training times.
Key Capabilities
- Instruction Following: Inherits and enhances the instruction-following capabilities of the base Qwen2.5-7B-Instruct model.
- Efficient Training: Benefits from the Unsloth framework, suggesting an optimized and potentially more resource-efficient fine-tuning process.
Good For
- Applications requiring a Qwen2.5-based model with a substantial context window.
- Developers looking for a model fine-tuned with efficient methods like Unsloth, potentially indicating a well-optimized and performant instruction-tuned LLM.