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Description

Training cutting-edge language models presents significant challenges; it demands vast computational resources, intricate distributed computing strategies, and substantial machine learning knowledge. Consequently, only a limited number of organizations embark on the journey of developing large language models (LLMs) from the ground up. Furthermore, many of those with the necessary capabilities and knowledge have begun to restrict access to their findings, indicating a notable shift from practices observed just a few months ago. At Cerebras, we are committed to promoting open access to state-of-the-art models. Therefore, we are excited to share with the open-source community the launch of Cerebras-GPT, which consists of a series of seven GPT models with parameter counts ranging from 111 million to 13 billion. Utilizing the Chinchilla formula for training, these models deliver exceptional accuracy while optimizing for computational efficiency. Notably, Cerebras-GPT boasts quicker training durations, reduced costs, and lower energy consumption compared to any publicly accessible model currently available. By releasing these models, we hope to inspire further innovation and collaboration in the field of machine learning.

Description

Llama (Large Language Model Meta AI) stands as a cutting-edge foundational large language model aimed at helping researchers push the boundaries of their work within this area of artificial intelligence. By providing smaller yet highly effective models like Llama, the research community can benefit even if they lack extensive infrastructure, thus promoting greater accessibility in this dynamic and rapidly evolving domain. Creating smaller foundational models such as Llama is advantageous in the landscape of large language models, as it demands significantly reduced computational power and resources, facilitating the testing of innovative methods, confirming existing research, and investigating new applications. These foundational models leverage extensive unlabeled datasets, making them exceptionally suitable for fine-tuning across a range of tasks. We are offering Llama in multiple sizes (7B, 13B, 33B, and 65B parameters), accompanied by a detailed Llama model card that outlines our development process while adhering to our commitment to Responsible AI principles. By making these resources available, we aim to empower a broader segment of the research community to engage with and contribute to advancements in AI.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

No images available

Integrations

Alpaca
AnythingLLM
Basalt
Chatbot Arena
Concierge AI
FalkorDB
Firecrawl
Gopher
Lakera
Llama 4 Maverick
Mastra AI
NudgeBee
Overseer AI
PromptPal
PromptSignal
RankLLM
SiliconFlow
Trusys AI
WebLLM
WriteFastly

Integrations

Alpaca
AnythingLLM
Basalt
Chatbot Arena
Concierge AI
FalkorDB
Firecrawl
Gopher
Lakera
Llama 4 Maverick
Mastra AI
NudgeBee
Overseer AI
PromptPal
PromptSignal
RankLLM
SiliconFlow
Trusys AI
WebLLM
WriteFastly

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

Cerebras

Founded

2015

Country

United States

Website

cerebras.ai/ai-model-services/

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

www.llama.com

Product Features

Alternatives

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Alpaca

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