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What is SmolLM2?

SmolLM2 features a sophisticated range of compact language models designed for effective on-device operations. This assortment includes models with various parameter counts, such as a substantial 1.7 billion, alongside more efficient iterations at 360 million and 135 million parameters, which guarantees optimal functionality on devices with limited resources. The models are particularly adept at text generation and have been fine-tuned for scenarios that demand quick responses and low latency, ensuring they deliver exceptional results in diverse applications, including content creation, programming assistance, and understanding natural language. The adaptability of SmolLM2 makes it a prime choice for developers who wish to embed powerful AI functionalities into mobile devices, edge computing platforms, and other environments where resource availability is restricted. Its thoughtful design exemplifies a dedication to achieving a balance between high performance and user accessibility, thus broadening the reach of advanced AI technologies. Furthermore, the ongoing development of such models signals a promising future for AI integration in everyday technology.

What is Llama 2?

We are excited to unveil the latest version of our open-source large language model, which includes model weights and initial code for the pretrained and fine-tuned Llama language models, ranging from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been crafted using a remarkable 2 trillion tokens and boast double the context length compared to the first iteration, Llama 1. Additionally, the fine-tuned models have been refined through the insights gained from over 1 million human annotations. Llama 2 showcases outstanding performance compared to various other open-source language models across a wide array of external benchmarks, particularly excelling in reasoning, coding abilities, proficiency, and knowledge assessments. For its training, Llama 2 leveraged publicly available online data sources, while the fine-tuned variant, Llama-2-chat, integrates publicly accessible instruction datasets alongside the extensive human annotations mentioned earlier. Our project is backed by a robust coalition of global stakeholders who are passionate about our open approach to AI, including companies that have offered valuable early feedback and are eager to collaborate with us on Llama 2. The enthusiasm surrounding Llama 2 not only highlights its advancements but also marks a significant transformation in the collaborative development and application of AI technologies. This collective effort underscores the potential for innovation that can emerge when the community comes together to share resources and insights.

Media

Media

Integrations Supported

Runpod

Integrations Supported

Runpod
ConfidentialMind
Cyte
DeepEval
Featherless
Fleak
Graydient AI
Kiin
Literal AI
Meta AI
Ollama
Prompt Security
Ragas
ReByte
Revere
Second State
SurePath AI
TESS AI
Taylor AI
WebLLM

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

Supported Platforms

Android
iPhone
iPad
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Hugging Face

Date Founded

2016

Company Location

United States

Company Website

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

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

ai.meta.com/llama/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

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