Model overview
This model is the first Polish-focused Vision-Language Model (VLM), created by extending the open-source LLaVA architecture with the Bielik language model. Our pipeline integrates high-quality multimodal instruction tuning with Bielik’s strong Polish linguistic abilities, resulting in a VLM that demonstrates significantly improved understanding of Polish language, culture, and context-specific visual reasoning. The model is intended for research and development purposes, specifically focusing on multimodal tasks requiring the Polish language and cultural context. It can be used directly for: This model can be fine-tuned or integrated into larger applications to support specific use cases, such as: * **Accessibility Tools:** Creating applications that describe surroundings or digital content to visually impaired Polish speakers. * **E-commerce:** Generating automated product descriptions based on images for Polish marketplaces. * **Educational Assistants:** Developing tutoring systems that can explain visual content (diagrams, historical photos) to students in Polish. * **Specialized Fine-tuning:** The model can be further fine-tuned on domain-specific datasets (e.g., Polish medical imaging reports or legal document analysis) to improve performance in niche sectors.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证：cc-by-nc-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。