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Description
StableCode provides an innovative solution for developers aiming to enhance their productivity through the utilization of three distinct models designed to assist in coding tasks. Initially, the foundational model was developed using a broad range of programming languages sourced from the stack-dataset (v1.2) by BigCode, with subsequent training focused on widely-used languages such as Python, Go, Java, JavaScript, C, Markdown, and C++. In total, our models have been trained on an impressive 560 billion tokens of code using our high-performance computing cluster.
Once the base model was created, an instruction model was meticulously fine-tuned for particular use cases, enabling it to tackle intricate programming challenges effectively. To achieve this refinement, approximately 120,000 pairs of code instructions and responses in Alpaca format were utilized to train the base model.
StableCode serves as a perfect foundation for those eager to deepen their understanding of programming, while the long-context window model provides an exceptional assistant that delivers both single-line and multi-line autocomplete suggestions seamlessly. This advanced model is specifically designed to efficiently manage larger chunks of code simultaneously, enhancing the overall coding experience for developers. By integrating these features, StableCode not only aids in coding but also fosters a deeper learning environment for aspiring programmers.
Description
StableVicuna represents the inaugural large-scale open-source chatbot developed through reinforced learning from human feedback (RLHF). It is an advanced version of the Vicuna v0 13b model, which has undergone further instruction fine-tuning and RLHF training. To attain the impressive capabilities of StableVicuna, we use Vicuna as the foundational model and adhere to the established three-stage RLHF framework proposed by Steinnon et al. and Ouyang et al. Specifically, we perform additional training on the base Vicuna model with supervised fine-tuning (SFT), utilizing a blend of three distinct datasets. The first is the OpenAssistant Conversations Dataset (OASST1), which consists of 161,443 human-generated messages across 66,497 conversation trees in 35 languages. The second dataset is GPT4All Prompt Generations, encompassing 437,605 prompts paired with responses created by GPT-3.5 Turbo. Lastly, the Alpaca dataset features 52,000 instructions and demonstrations that were produced using OpenAI's text-davinci-003 model. This collective approach to training enhances the chatbot's ability to engage effectively in diverse conversational contexts.
API Access
Has API
API Access
Has API
Integrations
C
C++
Go
Java
JavaScript
Python
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
Stability AI
Founded
2019
Country
United Kingdom
Website
stability.ai
Vendor Details
Company Name
Stability AI
Founded
2019
Country
United Kingdom
Website
stability.ai/
Product Features
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Chatbot
Call to Action
Context and Coherence
Human Takeover
Inline Media / Videos
Machine Learning
Natural Language Processing
Payment Integration
Prediction
Ready-made Templates
Reporting / Analytics
Sentiment Analysis
Social Media Integration
Conversational AI
Code-free Development
Contextual Guidance
For Developers
Intent Recognition
Multi-Languages
Omni-Channel
On-Screen Chats
Pre-configured Bot
Reusable Components
Sentiment Analysis
Speech Recognition
Speech Synthesis
Virtual Assistant