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What is Stable LM?

Stable LM signifies a notable progression in the language model domain, building upon prior open-source experiences, especially through collaboration with EleutherAI, a nonprofit research group. This evolution has included the creation of prominent models like GPT-J, GPT-NeoX, and the Pythia suite, all trained on The Pile open-source dataset, with several recent models such as Cerebras-GPT and Dolly-2 taking cues from this foundational work. In contrast to earlier models, Stable LM utilizes a groundbreaking dataset that is three times as extensive as The Pile, comprising an impressive 1.5 trillion tokens. More details regarding this dataset will be disclosed soon. The vast scale of this dataset allows Stable LM to perform exceptionally well in conversational and programming tasks, even though it has a relatively compact parameter size of 3 to 7 billion compared to larger models like GPT-3, which features 175 billion parameters. Built for adaptability, Stable LM 3B is a streamlined model designed to operate efficiently on portable devices, including laptops and mobile gadgets, which excites us about its potential for practical usage and portability. This innovation has the potential to bridge the gap for users seeking advanced language capabilities in accessible formats, thus broadening the reach and impact of language technologies. Overall, the launch of Stable LM represents a crucial advancement toward developing more efficient and widely available language models for diverse users.

What is GPT-NeoX?

This repository presents an implementation of model parallel autoregressive transformers that harness the power of GPUs through the DeepSpeed library. It acts as a documentation of EleutherAI's framework aimed at training large language models specifically for GPU environments. At this time, it expands upon NVIDIA's Megatron Language Model, integrating sophisticated techniques from DeepSpeed along with various innovative optimizations. Our objective is to establish a centralized resource for compiling methodologies essential for training large-scale autoregressive language models, which will ultimately stimulate faster research and development in the expansive domain of large-scale training. By making these resources available, we aspire to make a substantial impact on the advancement of language model research while encouraging collaboration among researchers in the field.

Media

Media

Integrations Supported

Alpaca
Automi
Gopher

Integrations Supported

Forefront
ZBrain

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Stability AI

Date Founded

2019

Company Location

United Kingdom

Company Website

stability.ai/

Company Facts

Organization Name

EleutherAI

Date Founded

2020

Company Website

github.com/EleutherAI/gpt-neox

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

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