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Description
FlowCoder serves as a WYSIWYG programming framework that facilitates the prototyping, debugging, validation, fuzzing, and testing of computer networks, encompassing functional, load, and security assessments. It empowers users to construct packets for diverse network protocols, transmit them across the network, and analyze incoming traffic while correlating requests with responses and managing states effectively. The most straightforward implementation occurs locally, where all packets generated by FlowCoder start from a local host, and any incoming replies are handled on the same machine. Only the components of the FlowCoder IDE operate locally, while the flowcharts created are dispatched to a cloud environment that runs multiple instances of the flowchart processing engine. In this cloud setting, packets are both created and processed, enabling users to receive diagnostic information and statistical insights. By acting as a man-in-the-middle (MITM) in the cloud, the flowchart can observe and manipulate packets that flow between two network endpoints, allowing modifications at any layer of the stack and enhancing the overall testing capabilities. This unique approach provides a comprehensive solution for network analysis and testing, making it an invaluable tool for developers and engineers alike.
Description
StarCoder and StarCoderBase represent advanced Large Language Models specifically designed for code, developed using openly licensed data from GitHub, which encompasses over 80 programming languages, Git commits, GitHub issues, and Jupyter notebooks. In a manner akin to LLaMA, we constructed a model with approximately 15 billion parameters trained on a staggering 1 trillion tokens. Furthermore, we tailored the StarCoderBase model with 35 billion Python tokens, leading to the creation of what we now refer to as StarCoder.
Our evaluations indicated that StarCoderBase surpasses other existing open Code LLMs when tested against popular programming benchmarks and performs on par with or even exceeds proprietary models like code-cushman-001 from OpenAI, the original Codex model that fueled early iterations of GitHub Copilot. With an impressive context length exceeding 8,000 tokens, the StarCoder models possess the capability to handle more information than any other open LLM, thus paving the way for a variety of innovative applications. This versatility is highlighted by our ability to prompt the StarCoder models through a sequence of dialogues, effectively transforming them into dynamic technical assistants that can provide support in diverse programming tasks.
API Access
Has API
API Access
Has API
Integrations
ChatGPT
CodeQwen
Git
GitHub
LM Studio
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code
Integrations
ChatGPT
CodeQwen
Git
GitHub
LM Studio
OpenAI
Python
Tabby
Taylor AI
Visual Studio Code
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
Omnipacket
Founded
2014
Website
omnipacket.com/flowcoder
Vendor Details
Company Name
BigCode
Founded
2023
Website
huggingface.co/blog/starcoder
Product Features
Network Automation
Compliance Monitoring
Configuration Backup
Configuration Changes
Network Orchestration
Performance Monitoring
Tool Access Control
Vulnerability Assessments