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Average Ratings 0 Ratings

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ease
features
design
support

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Description

SmolLM2 comprises an advanced suite of compact language models specifically created for on-device functionalities. This collection features models with varying sizes, including those with 1.7 billion parameters, as well as more streamlined versions at 360 million and 135 million parameters, ensuring efficient performance on even the most limited hardware. They excel in generating text and are fine-tuned for applications requiring real-time responsiveness and minimal latency, delivering high-quality outcomes across a multitude of scenarios such as content generation, coding support, and natural language understanding. The versatility of SmolLM2 positions it as an ideal option for developers aiming to incorporate robust AI capabilities into mobile devices, edge computing solutions, and other settings where resources are constrained. Its design reflects a commitment to balancing performance and accessibility, making cutting-edge AI technology more widely available.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Alpaca
Automi
Gopher
Hugging Face
Locally AI
Mirai
RunPod

Integrations

Alpaca
Automi
Gopher
Hugging Face
Locally AI
Mirai
RunPod

Pricing Details

Free
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

Hugging Face

Founded

2016

Country

United States

Website

huggingface.co/collections/HuggingFaceTB/smollm2-6723884218bcda64b34d7db9

Vendor Details

Company Name

Stability AI

Founded

2019

Country

United Kingdom

Website

stability.ai/

Product Features

Alternatives

Alternatives

Dolly Reviews

Dolly

Databricks
BitNet Reviews

BitNet

Microsoft
Cerebras-GPT Reviews

Cerebras-GPT

Cerebras
Orpheus TTS Reviews

Orpheus TTS

Canopy Labs
GPT-J Reviews

GPT-J

EleutherAI
Falcon-40B Reviews

Falcon-40B

Technology Innovation Institute (TII)