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Description
DeepGit provides a superior way to address the question "why is this code there?" compared to traditional Git clients by facilitating a thorough exploration of source code history. This innovative tool builds upon the git blame feature, enabling users to easily track modifications made to specific lines or segments of code. Notably, DeepGit excels in recognizing code movements, even when lines have undergone changes that render them non-identical. Furthermore, it is available for free, making it accessible for use in both personal and commercial settings. Users can seamlessly integrate DeepGit with various IDEs that support external tools, including popular platforms like Eclipse, Visual Studio, and IntelliJ IDEA, as well as robust text editors like Sublime. For those interested in mastering its functionalities, a tour is available to demonstrate how DeepGit operates effectively. Compatible with Windows, macOS, and Linux, DeepGit generates a blame report for the chosen file and conducts an analysis of the selected line and its surrounding context to trace its origin. It's important to note that the origin identified by DeepGit may not directly align with the corresponding left counterpart. Additionally, even when focusing on a single line, DeepGit often identifies a block of lines that serves as the best match for further investigation, enhancing the user's understanding of code evolution. This capability not only clarifies the rationale behind code changes but also aids developers in maintaining better code comprehension over time.
Description
DeepSeek-V2 is a cutting-edge Mixture-of-Experts (MoE) language model developed by DeepSeek-AI, noted for its cost-effective training and high-efficiency inference features. It boasts an impressive total of 236 billion parameters, with only 21 billion active for each token, and is capable of handling a context length of up to 128K tokens. The model utilizes advanced architectures such as Multi-head Latent Attention (MLA) to optimize inference by minimizing the Key-Value (KV) cache and DeepSeekMoE to enable economical training through sparse computations. Compared to its predecessor, DeepSeek 67B, this model shows remarkable improvements, achieving a 42.5% reduction in training expenses, a 93.3% decrease in KV cache size, and a 5.76-fold increase in generation throughput. Trained on an extensive corpus of 8.1 trillion tokens, DeepSeek-V2 demonstrates exceptional capabilities in language comprehension, programming, and reasoning tasks, positioning it as one of the leading open-source models available today. Its innovative approach not only elevates its performance but also sets new benchmarks within the field of artificial intelligence.
API Access
Has API
API Access
Has API
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Syntevo
Country
Germany
Website
www.syntevo.com/deepgit/
Vendor Details
Company Name
DeepSeek
Founded
2023
Country
China
Website
deepseek.com