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ease
features
design
support

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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

Screenshots View All

Screenshots View All

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

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