sithum8363/Architect_Assistant_Full
The sithum8363/Architect_Assistant_Full is a 0.5 billion parameter Qwen2.5-based instruction-tuned causal language model developed by sithum8363. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. With a 32768 token context length, it is optimized for efficient performance in instruction-following tasks.
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Model Overview
The sithum8363/Architect_Assistant_Full is a 0.5 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by sithum8363, this model was fine-tuned using the Unsloth framework in conjunction with Huggingface's TRL library, which facilitated a 2x speedup in the training process. It offers a substantial context length of 32768 tokens, making it suitable for processing longer inputs and maintaining conversational coherence over extended interactions.
Key Capabilities
- Efficient Instruction Following: Fine-tuned for understanding and executing instructions effectively.
- Optimized Training: Leverages Unsloth for faster and more resource-efficient fine-tuning.
- Extended Context: Supports a 32768 token context window, beneficial for complex queries or multi-turn conversations.
Good For
- Applications requiring a compact yet capable instruction-tuned model.
- Scenarios where efficient inference and a large context window are advantageous.
- Developers looking for a Qwen2.5-based model with optimized training origins.