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Description

ESMFold demonstrates how artificial intelligence can equip us with innovative instruments to explore the natural world, akin to the way the microscope revolutionized our perception by allowing us to observe the minute details of life. Through AI, we can gain a fresh perspective on the vast array of biological diversity, enhancing our comprehension of life sciences. A significant portion of AI research has been dedicated to enabling machines to interpret the world in a manner reminiscent of human understanding. However, the complex language of proteins remains largely inaccessible to humans and has proven challenging for even the most advanced computational systems. Nevertheless, AI holds the promise of unlocking this intricate language, facilitating our grasp of biological processes. Exploring AI within the realm of biology not only enriches our understanding of life sciences but also sheds light on the broader implications of artificial intelligence itself. Our research highlights the interconnectedness of various fields: the large language models powering advancements in machine translation, natural language processing, speech recognition, and image synthesis also possess the capability to assimilate profound insights about biological systems. This cross-disciplinary approach could pave the way for unprecedented discoveries in both AI and biology.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

Admix No 
Alumnium No 
Amazon Bedrock No 
AnythingLLM No 
Astera AI Agent Builder No 
Athina AI No 
Azure Marketplace No 
Bolna No 
Cherry Studio No 
Decopy AI No 
EaseMate AI No 
Lakera No 
Llama 4 Behemoth No 
Lorelight No 
Nebius Token Factory No 
NudgeBee No 
Nutanix Enterprise AI No 
Ollama No 
Void Editor No 
Waveloom No 

Integrations

Admix Yes 
Alumnium Yes 
Amazon Bedrock Yes 
AnythingLLM Yes 
Astera AI Agent Builder Yes 
Athina AI Yes 
Azure Marketplace Yes 
Bolna Yes 
Cherry Studio Yes 
Decopy AI Yes 
EaseMate AI Yes 
Lakera Yes 
Llama 4 Behemoth Yes 
Lorelight Yes 
Nebius Token Factory Yes 
NudgeBee Yes 
Nutanix Enterprise AI Yes 
Ollama Yes 
Void Editor Yes 
Waveloom Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
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

github.com/facebookresearch/esm

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

www.llama.com

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