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What is distil labs?

Distil Labs improves the efficiency of AI by replacing expensive calls to sophisticated models with custom small language models tailored for particular tasks, all while maintaining high-quality benchmarks. They analyze real production traffic and collect traces from current large language model requests to create a comprehensive evaluation set that reveals genuine workload characteristics. Subsequently, the company develops and validates synthetic training data, ensuring that its distribution aligns with the desired workload, and employs supervised fine-tuning in conjunction with reinforcement learning techniques. Once the model is quantized, an optimized endpoint is created to support its deployment. The results are rigorously compared to the existing model in terms of accuracy, latency, and overall efficiency, offering teams the information necessary to decide when to scale up traffic. Furthermore, the OpenAI-compatible endpoint incorporates a specialized small language model, prompt optimization, efficient caching, and enhanced serving tailored for specific applications, thereby guaranteeing optimal performance. By adopting this thorough methodology, organizations are empowered to fully leverage the capabilities of their AI solutions, ultimately driving greater innovation and effectiveness within their operations.

What is Llama?

Llama, a leading-edge foundational large language model developed by Meta AI, is designed to assist researchers in expanding the frontiers of artificial intelligence research. By offering streamlined yet powerful models like Llama, even those with limited resources can access advanced tools, thereby enhancing inclusivity in this fast-paced and ever-evolving field. The development of more compact foundational models, such as Llama, proves beneficial in the realm of large language models since they require considerably less computational power and resources, which allows for the exploration of novel approaches, validation of existing studies, and examination of potential new applications. These models harness vast amounts of unlabeled data, rendering them particularly effective for fine-tuning across diverse tasks. We are introducing Llama in various sizes, including 7B, 13B, 33B, and 65B parameters, each supported by a comprehensive model card that details our development methodology while maintaining our dedication to Responsible AI practices. By providing these resources, we seek to empower a wider array of researchers to actively participate in and drive forward the developments in the field of AI. Ultimately, our goal is to foster an environment where innovation thrives and collaboration flourishes.

Media

Media

No images available

Integrations Supported

AICamp
Atomic Chat
CompactifAI
Decopy AI
EaseMate AI
FalkorDB
Featherless
GPT for Work
Jitterbit
Klee
LFM2.5
Locally AI
NVIDIA Llama Nemotron
Pinecone Rerank v0
Prompt Genie
PromptPal
Scottie
SpyderBot
WriteFastly
ZenML

Integrations Supported

AICamp
Atomic Chat
CompactifAI
Decopy AI
EaseMate AI
FalkorDB
Featherless
GPT for Work
Jitterbit
Klee
LFM2.5
Locally AI
NVIDIA Llama Nemotron
Pinecone Rerank v0
Prompt Genie
PromptPal
Scottie
SpyderBot
WriteFastly
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

$0.04 per 1M tokens
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

distil labs

Date Founded

2024

Company Location

Germany

Company Website

www.distillabs.ai/

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

www.llama.com

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