wooodpecker22/icp-assistant-model_qwen_3
The icp-assistant-model_qwen_3 is a 7.6 billion parameter Qwen2-based instruction-tuned causal language model developed by wooodpecker22. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging the Qwen2.5 architecture for efficient performance.
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Model Overview
The icp-assistant-model_qwen_3 is a 7.6 billion parameter instruction-tuned language model, developed by wooodpecker22. It is based on the Qwen2 architecture, specifically fine-tuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Utilizes the Qwen2.5 base model, known for its strong performance across various language tasks.
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Context Length: Supports a context window of 32768 tokens, allowing for processing and generating longer sequences of text.
Use Cases
This model is suitable for a range of instruction-following applications, benefiting from its efficient training and robust base architecture. Its capabilities make it a strong candidate for tasks requiring general language understanding and generation, particularly where the Qwen2.5 family has demonstrated proficiency.