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Description

Introducing the next iteration of our open-source large language model, this version features model weights along with initial code for the pretrained and fine-tuned Llama language models, which span from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been developed using an impressive 2 trillion tokens and offer double the context length compared to their predecessor, Llama 1. Furthermore, the fine-tuned models have been enhanced through the analysis of over 1 million human annotations. Llama 2 demonstrates superior performance against various other open-source language models across multiple external benchmarks, excelling in areas such as reasoning, coding capabilities, proficiency, and knowledge assessments. For its training, Llama 2 utilized publicly accessible online data sources, while the fine-tuned variant, Llama-2-chat, incorporates publicly available instruction datasets along with the aforementioned extensive human annotations. Our initiative enjoys strong support from a diverse array of global stakeholders who are enthusiastic about our open approach to AI, including companies that have provided valuable early feedback and are eager to collaborate using Llama 2. The excitement surrounding Llama 2 signifies a pivotal shift in how AI can be developed and utilized collectively.

Description

Distil Labs enhances AI performance by substituting costly calls to advanced models with tailored small language models designed for specific tasks while ensuring the quality standards are upheld. By monitoring real production traffic and gathering traces from current LLM requests, it constructs an evaluation set to gain insights into actual workload behavior. Following this, the company creates and verifies synthetic training data, aligns the data distribution with the intended workload, and engages in supervised fine-tuning alongside reinforcement learning. The model is then quantized, and an optimized endpoint is established. The outcomes are systematically assessed against the existing model concerning accuracy, latency, and efficiency, providing teams with data to determine when to increase traffic. Ultimately, the OpenAI-compatible endpoint features a specialized small language model, prompt optimization, effective caching, and refined serving tailored for the specific application, ensuring maximum performance. This comprehensive approach allows organizations to maximize the potential of their AI implementations.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AiAssistWorks
Browser Use
Chatterbox
Coginiti
DataChain
Ema
GMTech
GPT-5.4 nano
Jspreadsheet
Kiin
Lakera
Microsoft Foundry Models
Preamble
PromptPal
Revere
Solar Mini
Taylor AI
Tune AI
Waveloom

Integrations

AiAssistWorks
Browser Use
Chatterbox
Coginiti
DataChain
Ema
GMTech
GPT-5.4 nano
Jspreadsheet
Kiin
Lakera
Microsoft Foundry Models
Preamble
PromptPal
Revere
Solar Mini
Taylor AI
Tune AI
Waveloom

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0.04 per 1M tokens
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

Meta

Founded

2004

Country

United States

Website

ai.meta.com/llama/

Vendor Details

Company Name

distil labs

Founded

2024

Country

Germany

Website

www.distillabs.ai/

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