360Zhinao2-7B - 360 launches an upgraded version of its self-developed 360 Smart Brain Big Model.

What is 360Zhinao2-7B?

360Zhinao2-7B is an upgraded version of 360's self-developed AI large-scale model, 360 Brain 7B, encompassing both basic models and chat models with varying context lengths. The 360Zhinao2-7B model represents a significant update to 360Zhinao1-7B, employing a new multi-stage training method and superior data processing strategies to enhance its Chinese and English compatibility and mathematical reasoning capabilities. Among open-source models of similar size both domestically and internationally, 360Zhinao2-7B ranks first in Chinese language proficiency, adherence to the 7B IFEval instruction, and complex mathematical reasoning abilities. Its long-text fine-tuning capabilities also rank among the top in various long-text benchmarks.

Main functions of 360Zhinao2-7B

• Language comprehension and generationIt can understand and generate Chinese and English text, and is suitable for a variety of language processing tasks.
• Chatting skillsIt offers powerful chat features, supporting the generation of fluent, relevant, and accurate dialogue responses.
• Multiple context length supportChat models with different context lengths can handle conversation history of varying lengths from 4K to 360K.
• Mathematical logical reasoningThey excel in solving mathematical problems and logical reasoning, and are able to handle complex mathematical problems.
• Multilingual supportIn addition to Chinese, the model also supports English, enabling training and inference on datasets in different languages.
• Business applicationsIt supports free commercial use and is suitable for multiple business scenarios such as education, healthcare, and intelligent customer service.

Technical Principles of 360Zhinao2-7B

• Large-scale pre-training:
  • Two-stage training methodFirst, we train on a large-scale, undifferentiated dataset, and then we increase the proportion of high-quality data for the second stage of training.
  • Training with large amounts of dataThe model training involves a first-stage training of 10T (trillion) tokens and a second-stage training of 100B (hundred billion) tokens.
• Transformer architectureBased on the Transformer architecture, it is a deep learning model that is widely used in natural language processing tasks.
• Self-attention mechanismThe model uses a self-attention mechanism to process each element in the input sequence, enabling it to understand the complex relationships between words or phrases.
• Context modelingThe chat model supports contexts of varying lengths and can generate responses based on the conversation history, requiring the model to have good context modeling capabilities.
• Optimization strategy:
  • Learning rate scheduling: Optimize the training process using learning rate scheduling strategies such as cosine annealing.
  • Mixed precision trainingIt employs hybrid precision training techniques such as BF16 (Brain Floating Point 16) to improve training efficiency and reduce memory usage.

Project address of 360Zhinao2-7B

• GitHub repository:https://github.com/Qihoo360/360zhinao2
• HuggingFace model library:https://huggingface.co/collections/qihoo360/360zhinao2

Application scenarios of 360Zhinao2-7B

• Intelligent Customer ServiceIt provides automated customer consultation services, answers user questions, and improves customer service efficiency.
• Educational SupportAs a teaching aid, it provides language learning support and helps students understand complex concepts.
• Content creationIt assists in writing and content generation, such as writing articles and generating creative copy.
• Language translationAs a machine translation tool, it enables automatic translation between different languages.
• Information retrievalImprove the search engine to provide more accurate search results and information recommendations.