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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
Stable LM represents a significant advancement in the field of language models by leveraging our previous experience with open-source initiatives, particularly in collaboration with EleutherAI, a nonprofit research organization. This journey includes the development of notable models such as GPT-J, GPT-NeoX, and the Pythia suite, all of which were trained on The Pile open-source dataset, while many contemporary open-source models like Cerebras-GPT and Dolly-2 have drawn inspiration from this foundational work. Unlike its predecessors, Stable LM is trained on an innovative dataset that is three times the size of The Pile, encompassing a staggering 1.5 trillion tokens. We plan to share more information about this dataset in the near future. The extensive nature of this dataset enables Stable LM to excel remarkably in both conversational and coding scenarios, despite its relatively modest size of 3 to 7 billion parameters when compared to larger models like GPT-3, which boasts 175 billion parameters. Designed for versatility, Stable LM 3B is a streamlined model that can efficiently function on portable devices such as laptops and handheld gadgets, making us enthusiastic about its practical applications and mobility. Overall, the development of Stable LM marks a pivotal step towards creating more efficient and accessible language models for a wider audience.
API Access
Has API
No
API Access
Has API
No
Integrations
Alpaca
No
Automi
No
C
Yes
C++
Yes
Go
Yes
Gopher
No
Java
Yes
JavaScript
Yes
Python
Yes
Integrations
Alpaca
Yes
Automi
Yes
C
No
C++
No
Go
No
Gopher
Yes
Java
No
JavaScript
No
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
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/
