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ease
features
design
support

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Description

Cut down on administrative expenses and enhance reimbursement rates, all while ensuring compliance is upheld. Transform your revenue cycle management (RCM) with the innovative capabilities of RapidClaims powered by AI technology. Significantly reduce administrative costs, elevate reimbursement levels, and maintain compliance with minimal effort. Simplify your coding workflow, and either automate tasks or empower your coding staff with tailored solutions that meet your specific needs. Process thousands of charts quickly and accurately while addressing the distinct demands of each client. Our advanced language model adeptly handles unstructured data, crafting a comprehensive patient record by turning notes into organized codes and identifying disease patterns. Avoid repeating past errors by establishing broad coding-related rules in straightforward language, which can be easily implemented across your charts, categorized by specialty, code type, and individual coders. Enhance your insight into code-level trends across various locations and take proactive steps to refine the revenue cycle. Additionally, our platform meticulously reviews charts to uncover claim denial trends, equipping you with the tools to address these challenges effectively and improve overall performance. With these capabilities, you can ensure a more streamlined and efficient coding process that supports your organization's financial health.

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

Better
CodeQwen
DrChrono
Elation Health
Git
GitHub
Google Cloud Platform
LM Studio
MEDITECH Expanse
Microsoft 365
NEON
OpenAI
Python
Taam Cloud
Tabby
Taylor AI
Together AI
Visual Studio Code
athenaOne
eClinicalWorks

Integrations

Better
CodeQwen
DrChrono
Elation Health
Git
GitHub
Google Cloud Platform
LM Studio
MEDITECH Expanse
Microsoft 365
NEON
OpenAI
Python
Taam Cloud
Tabby
Taylor AI
Together AI
Visual Studio Code
athenaOne
eClinicalWorks

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

RapidClaims

Country

United States

Website

www.rapidclaims.ai/

Vendor Details

Company Name

BigCode

Founded

2023

Website

huggingface.co/blog/starcoder

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