jpalmae/qwen35b-espanol-abl-merged-v3
jpalmae/qwen35b-espanol-abl-merged-v3 is a 35.1 billion parameter multimodal Qwen3.5/3.6 model developed by jpalmae, specifically fine-tuned for neutral and Chilean Spanish. This model incorporates a unique anti-Rioplatense filtering during training, making it distinctively optimized for specific Spanish dialects. It maintains multimodal capabilities, including vision configuration and support for image/video tokens, making it suitable for applications requiring nuanced Spanish language understanding and multimodal input processing.
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Model Overview
The jpalmae/qwen35b-espanol-abl-merged-v3 is a 35.1 billion parameter multimodal language model, built upon the Qwen3.5/3.6 35B-A3B architecture. Developed by jpalmae, this model is a merged version that has undergone specialized training to cater to neutral and Chilean Spanish, with a notable anti-Rioplatense filtering applied during its dataset preparation.
Key Capabilities & Features
- Multimodal Architecture: Retains full multimodal capabilities, including
vision_configand support for image/video tokens, allowing for processing of diverse input types. - Spanish Dialect Specialization: Fine-tuned with a custom dataset of 200,000 examples, including 60,000 Chilean, 60,000 neutral, and 80,000 anti-Rioplatense filtered examples, ensuring high relevance for target dialects.
- Training Details: Utilizes LoRA (r=64, alpha=128) for efficient fine-tuning over 2,500 steps, achieving a final loss of approximately 2.11.
- Deployment Ready: Designed for deployment with vLLM, indicating optimized inference performance.
When to Use This Model
This model is particularly well-suited for applications requiring:
- Accurate Spanish Generation: Specifically for neutral and Chilean Spanish contexts, where dialectal nuances are important.
- Multimodal Understanding: For tasks that involve both text and visual inputs in Spanish.
- Regional Content Creation: Ideal for generating content, chatbots, or virtual assistants tailored to Chilean or general neutral Spanish-speaking audiences, avoiding Rioplatense linguistic characteristics.