Unveiling BizGen: 2.7B parameter model helps generate commercial copy, increasing efficiency by 3 times

In the digital age, high-quality business copywriting has become a core asset for corporate competition. How to generate creative, professional and business-contextual copywriting in a short period of time has always been a pain point that the market needs to solve. Recently, Microsoft Research Asia (MSRA) launched the open source large model  BizGen , which has achieved a breakthrough performance of 3 times the efficiency of business copywriting generation with its 2.7B parameter scale and training strategies customized for business texts.

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Model Overview: Focus on Business Text Generation

BizGen is an open-source large model designed for commercial text generation tasks, with a parameter scale of 2.7B. Compared with general language models, BizGen collects a large amount of data such as commercial copywriting, marketing promotion, and product introductions during pre-training and fine-tuning to ensure that the generated text is not only semantically coherent, but also accurate in style and meets business needs. Its main advantages include:

• Efficient generation : Among similar models, BizGen significantly improves the speed of copywriting generation. Experimental data shows that the generation efficiency is increased by about 3 times.
• Professional customization : The model is deeply optimized for business scenarios, and the generated text is more professional in logic, expression, and marketing context.
• Open source deployment : As an open source project, BizGen provides developers and enterprises with flexible secondary development and integration capabilities, helping smart marketing and enterprise digital transformation.

Core architecture and technical details

1. Transformer architecture and commercial corpus fine-tuning

BizGen uses the classic Transformer architecture and uses the self-attention mechanism to capture long-range dependencies, which gives it a natural advantage in language generation tasks. The difference is that BizGen introduced a large amount of carefully annotated business corpus during the pre-training phase, covering multiple scenarios such as advertising copy, business emails, and product descriptions. In this way, the model not only learns basic language expressions, but also accurately grasps the style and logic of the business context.

2. Multi-task joint learning

In order to further improve the generation quality of the model, BizGen adopted a multi-task joint learning strategy during the fine-tuning process, integrating tasks such as text summarization, sentiment analysis, and style transfer into the training. This strategy enables the model to not only focus on the richness of content when generating commercial copy, but also take into account emotional tendencies and brand tonality, ensuring that the output results are more persuasive and market competitive.

3. Efficient decoding strategy

In the generation phase, BizGen uses adaptive sampling and beam search technology to effectively improve the generation speed while ensuring the diversity of generated text. Experimental data shows that under the same hardware configuration, BizGen's response speed far exceeds that of traditional general language models, providing strong support for real-time text generation in commercial application scenarios.

Performance indicators and data support

BizGen demonstrated outstanding performance in multiple benchmark tests. Key data include:

• Generation efficiency : In standard copywriting generation tasks, BizGen's average generation time is 67% shorter than that of traditional models, which means that the efficiency is improved by about 3 times.
• Text quality : As evaluated by ROUGE and BLEU, BizGen performs significantly better than general models in business text generation tasks, and its text coherence and logic are both at the industry-leading level.
• Professional adaptability : In actual application scenario tests, the generated commercial copy is highly consistent with manual copy in terms of tone, expression and marketing strategy, and the average score of expert reviewers reached 4.6 (out of 5 points).

Application scenarios and practical cases

BizGen's powerful generation capabilities have brought revolutionary changes to a variety of business application scenarios:

• Marketing and Advertising Creative  Companies can use BizGen to quickly generate various advertising copy, slogans and social media content to improve marketing efficiency and reduce creative costs.
• E-commerce product descriptions and detail pages  use BizGen to automatically generate attractive and professional product descriptions, which not only improves user experience but also promotes the increase of conversion rate.
•  BizGen also excels in generating business emails and reports with rigorous style and clear logic, helping companies improve communication efficiency.
• Content Creation and Intelligent Customer Service  In content marketing and intelligent customer service systems, BizGen can provide users with high-quality, personalized answers and suggestions to further optimize the user experience.

Conclusion

With the in-depth application of artificial intelligence in the business field, how to efficiently generate professional copywriting has become the key to improving the competitiveness of enterprises. As the latest masterpiece of Microsoft Research Asia, BizGen has achieved a breakthrough of 3 times the efficiency of commercial copywriting generation with a 2.7B parameter scale and excellent generation performance, bringing a new revolution to marketing, e-commerce content and corporate business communication. We sincerely invite developers to download and experience it at HuggingFace, and continue to explore more application possibilities of BizGen in practice. In the future, with the continuous iteration and optimization of technology, BizGen will inject stronger power into enterprise intelligent transformation and business innovation.