DeepSeek-V2.5-1210
by DeepSeek AIDeepSeek-V2.5-1210 is the final fine-tuned model of DeepSeek V2.5, based on Post-Training iteration, which improves performance in math, programming, writing, and role-playing. It supports online search functionality, providing comprehensive, accurate, and personalized answers on the web, automatically extracting keywords for parallel searches, and delivering diverse results quickly. The model weights are open-sourced on Huggingface for developers and researchers.
What is DeepSeek-V2.5-1210?
DeepSeek-V2.5-1210 is the final fine-tuned model of DeepSeek V2.5, based on Post-Training iteration, which improves performance in math, programming, writing, and role-playing. It supports online search functionality, providing comprehensive, accurate, and personalized answers on the web, automatically extracting keywords for parallel searches, and delivering diverse results quickly. The model weights are open-sourced on Huggingface for developers and researchers.
Main Features of DeepSeek-V2.5-1210
- Enhanced Capabilities: Based on Post-Training iteration, the model has improved performance in math problem-solving, programming, writing, and role-playing.
- Online Search: Supports online search functionality, providing comprehensive, accurate, and personalized answers on the web.
- File Upload Optimization: Optimized file upload functionality to enhance user experience.
- Automatic Keyword Extraction: In online search mode, the model automatically extracts multiple keywords from user queries for more accurate search results.
- Quick Results Delivery: Delivers diverse and comprehensive results quickly, improving problem-solving efficiency.
Technical Principles of DeepSeek-V2.5-1210
- Pre-training and Fine-tuning: The model is first pre-trained on a large dataset to learn the basic structure and patterns of language. Fine-tuning further trains the model on specific tasks or domains to improve performance.
- Post-Training Iteration: After pre-training, DeepSeek-V2.5-1210 is further optimized through Post-Training iteration to enhance performance in specific areas.
- Self-attention Mechanism: The self-attention mechanism allows the model to consider the entire input sequence when processing a word or phrase, helping to capture longer-range dependencies.
Project Address of DeepSeek-V2.5-1210
- HuggingFace Model Library: https://huggingface.co/deepseek-ai/DeepSeek-V2.5-1210
Application Scenarios of DeepSeek-V2.5-1210
- Customer Service and Support: Acts as a chatbot, providing 24/7 online customer support, answering user questions, and handling common queries.
- Education and Learning: Assists in teaching, offering personalized learning advice and answering questions to help students understand complex concepts.
- Programming and Development: Aids in software development, providing code generation, debugging support, and best practice recommendations.
- Content Creation and Writing: Assists in writing articles, reports, and creative content, offering language proofreading and style improvements.
- Data Analysis and Research: Helps researchers analyze large datasets, extract key information, and support decision-making.
Model Capabilities
Model Type
language
Supported Tasks
Math Problem-Solving
Programming
Writing
Role-Playing
Online Search
Tags
AI Model
Fine-Tuning
Online Search
Natural Language Processing
Math Problem-Solving
Programming
Content Creation
Role-Playing
Open Source
Huggingface
Usage & Integration
Pricing
free
License
Open Source
Model Agreement
Requirements
- Python 3.8+
- 80GB*8 GPUs for BF16 inference
Screenshots & Images
Primary Screenshot
Additional Images
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