What is BlueLM
BlueLM is a new self-developed general large model matrix released by vivo, including a language large model, an on-device large model, a speech large model, an image large model, and a multimodal large model. It plays an important role in multiple fields and scenarios, such as content creation assistance, knowledge question-answering systems, logical reasoning and analysis, code generation and software development, information extraction and data analysis, automated office work, multilingual translation and localization, and creative entertainment.
BlueLM's model matrix
- BlueLM On-Device Large Model 3B: An on-device large model with 3 billion parameters, focused on running on mobile devices. It performs excellently in capabilities such as dialogue writing, summarization, and information extraction, comparable to a 7B-parameter large model. Compared with the previous generation, the 3B model improves performance by 300%, while reducing power consumption by 46% in balanced mode and reducing memory usage by 63%, achieving an extreme word output speed of 80 characters per second, with system power consumption of only 450mA and memory usage of only 1.4GB. It ranks among the top in the SuperCLUE and Equal Eval small model comprehensive capability evaluations, and has won the CTTL Terminal Labs on-device large model comprehensive capability certification and the AIIA security prevention capability certification.
- BlueLM Speech Large Model: The model can accurately understand natural semantics, simulate human voices, and express emotions. It supports simultaneous interpretation and adds support for dialects such as Sichuan dialect, Miao language, and Cantonese, further expanding the scope of services.
- BlueLM Image Large Model: The model strengthens the integrated generation capability of Chinese characteristics and Eastern aesthetics, supports Chinese-style ink art, and can incorporate Chinese character elements into the image generation process. It is one of the image models in China that best understands the Chinese context.
- BlueLM Multimodal Large Model: The model upgrades visual perception and understanding capabilities, can achieve a deeper understanding of mobile phone screens, and provides a smoother and more natural experience in real-time conversations with video streams.
Main functions of BlueLM
- Content creation: BlueLM can assist users in text creation, including writing articles, blogs, poems, and stories.
- Knowledge question-answering: The model can quickly provide question-answering services for general life knowledge and professional knowledge, helping users obtain the information they need.
- Logical reasoning: BlueLM can perform complex logical reasoning, including thinking reasoning, common sense reasoning, and scientific reasoning.
- Code generation: The model has code generation capabilities, helping developers write and optimize code.
- Information extraction: BlueLM can extract key information from large amounts of text, suitable for data analysis and information management.
- Multilingual support: The model supports multilingual processing and provides translation and localization services.
Technical principles of BlueLM
- Deep learning frameworks: BlueLM uses deep learning frameworks such as TensorFlow or PyTorch to build and train its complex neural networks.
- Large-scale pretraining: The model is pretrained on large amounts of text data to learn language patterns and structures, using the Transformer architecture, a model structure that performs excellently in NLP tasks.
- Attention mechanism: The attention mechanism in the Transformer model enables the model to better understand and handle the relationships between different parts of the input data.
- Fine-tuning: Building on pre-training, the model is fine-tuned on specific tasks to improve its performance on those tasks.
- End-to-end learning: The BlueLM adopts an end-to-end learning approach, where the entire process from input to output is continuous and requires no human intervention.
Project addresses of the BlueLM
- Project official website：developers.vivo.com/product/ai/bluelm
- GitHub repository:https://github.com/vivo-ai-lab
- HuggingFace model library：https://huggingface.co/vivo-ai
Application scenarios of the BlueLM
- Content creation assistance: BlueLM can help users generate creative text, write articles or blogs, and even create poems and stories, improving writing efficiency and quality.
- Knowledge question-answering system: In the fields of education and research, BlueLM can provide accurate knowledge question-answering services, helping learners and researchers quickly obtain the information they need.
- Logical reasoning and analysis: In fields such as law and finance that require complex logical reasoning, BlueLM can analyze and solve complex logical problems and assist in decision-making.
- Code generation and software development: For programmers and software developers, BlueLM can assist in writing and optimizing code, improving development efficiency.
- Information extraction and data analysis: In the fields of big data analysis and information management, BlueLM can quickly extract key information from large amounts of text, facilitating data analysis and report creation.
- Automated office work: In daily office environments, BlueLM can help write and edit official documents and reports, and even automatically generate meeting minutes and email replies.