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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.

Description

Foundation models, including GPT-4, have significantly accelerated advancements in artificial intelligence, yet the most advanced models remain either proprietary or only partially accessible. In response to this challenge, the RedPajama initiative aims to develop a collection of top-tier, fully open-source models. We are thrilled to announce that we have successfully completed the initial phase of this endeavor: recreating the LLaMA training dataset, which contains over 1.2 trillion tokens. Currently, many of the leading foundation models are locked behind commercial APIs, restricting opportunities for research, customization, and application with sensitive information. The development of fully open-source models represents a potential solution to these limitations, provided that the open-source community can bridge the gap in quality between open and closed models. Recent advancements have shown promising progress in this area, suggesting that the AI field is experiencing a transformative period akin to the emergence of Linux. The success of Stable Diffusion serves as a testament to the fact that open-source alternatives can not only match the quality of commercial products like DALL-E but also inspire remarkable creativity through the collaborative efforts of diverse communities. By fostering an open-source ecosystem, we can unlock new possibilities for innovation and ensure broader access to cutting-edge AI technology.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

WebLLM Yes 
Athina AI Yes 
Decompute Blackbird Yes 
Diploria AI Yes 
Evertune Yes 
Firecrawl Yes 
Kong AI Gateway Yes 
NVIDIA DGX Cloud Serverless Inference Yes 
NativeMind Yes 
Private Mind Yes 
PyMuPDF Yes 
Ragas Yes 
Saptiva AI Yes 
SheetMagic Yes 
Snack Prompt Yes 
Teneo.AI Yes 
Teradata VantageCloud Yes 
Tune AI Yes 
UndetectedGPT Yes 
Unsloth Yes 

Integrations

WebLLM Yes 
Athina AI No 
Decompute Blackbird No 
Diploria AI No 
Evertune No 
Firecrawl No 
Kong AI Gateway No 
NVIDIA DGX Cloud Serverless Inference No 
NativeMind No 
Private Mind No 
PyMuPDF No 
Ragas No 
Saptiva AI No 
SheetMagic No 
Snack Prompt No 
Teneo.AI No 
Teradata VantageCloud No 
Tune AI No 
UndetectedGPT No 
Unsloth 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 Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 

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

Meta

Founded

2004

Country

United States

Website

www.llama.com

Vendor Details

Company Name

RedPajama

Founded

2023

Website

www.together.xyz/blog/redpajama

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