xCloudinfo/Gemma-4-26B-A4B-TAIDE-zhTW
xCloudinfo/Gemma-4-26B-A4B-TAIDE-zhTW is a 26 billion parameter multimodal language model developed by xCloudinfo, based on Google's Gemma-4-26B-A4B-it architecture. This model is specifically fine-tuned with TAIDE-distilled traditional Chinese (Taiwan) self-instruct data, retaining its native image recognition capabilities. It excels in image-text-to-text tasks and conversational AI in traditional Chinese, making it suitable for applications requiring both visual understanding and nuanced Taiwanese Mandarin interaction.
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Overview
xCloudinfo/Gemma-4-26B-A4B-TAIDE-zhTW is a 26 billion parameter multimodal model, developed by xCloudinfo, that specializes in traditional Chinese (Taiwan) language processing. It is built upon Google's gemma-4-26B-A4B-it base model, which features a 128-expert MoE architecture and supports both text and vision modalities. The model has been fine-tuned using bf16 LoRA SFT with a cleaned dataset of 27,955 traditional Chinese self-instruct entries, distilled from TAIDE models.
Key Capabilities
- Multimodal Understanding: Retains the base model's native image recognition capabilities, allowing for image-text-to-text generation. The LoRA fine-tuning specifically targeted the language model, leaving the vision tower unchanged.
- Traditional Chinese (Taiwan) Optimization: Specifically trained on TAIDE-derived data, making it highly proficient in Taiwanese Mandarin nuances and context.
- Efficient Fine-tuning: Utilizes bf16 LoRA for fine-tuning, which was then merged back into the full model.
Good For
- Applications requiring multimodal conversational AI in traditional Chinese, particularly for the Taiwanese market.
- Use cases involving image-text understanding and generation where traditional Chinese output is critical.
- Developers looking for a robust model with integrated vision capabilities and strong performance in a specific regional language variant.