yabu1608/qwen2.5-3b-hawassa-university-chatbot-q8
The yabu1608/qwen2.5-3b-hawassa-university-chatbot-q8 is a 3.1 billion parameter Qwen2.5-Instruct model, fine-tuned and converted to GGUF format. This model is optimized for chatbot applications, leveraging its instruction-tuned base for conversational tasks. It is designed for efficient deployment and use with tools like llama-cli and Ollama, making it suitable for local inference on various hardware.
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Model Overview
The yabu1608/qwen2.5-3b-hawassa-university-chatbot-q8 is a 3.1 billion parameter language model based on the Qwen2.5-Instruct architecture. This specific iteration has been fine-tuned for chatbot functionalities, making it adept at understanding and generating conversational responses. It is provided in the GGUF format, which is highly compatible with various inference engines.
Key Characteristics
- Architecture: Based on the Qwen2.5-Instruct model, known for its strong performance in instruction-following tasks.
- Parameter Count: Features 3.1 billion parameters, offering a balance between performance and computational efficiency.
- GGUF Format: Converted to GGUF using Unsloth, ensuring broad compatibility with tools like
llama-cppandOllama. - Fine-tuned for Chatbot Use: Specifically optimized for conversational AI applications, enhancing its ability to engage in dialogue.
- Efficient Training: The fine-tuning process was accelerated using Unsloth, indicating potential for efficient further customization.
Deployment and Usage
This model is designed for straightforward deployment. An Ollama Modelfile is included, simplifying its integration into Ollama environments. It can be used with llama-cli for text-only interactions or llama-mtmd-cli for multimodal applications, leveraging its instruction-tuned capabilities for various prompts.