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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-Factory?

LLaMA-Factory represents a cutting-edge open-source platform designed to streamline and enhance the fine-tuning process for over 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It offers diverse fine-tuning methods, including Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, allowing users to customize models effortlessly. The platform has demonstrated impressive performance improvements; for instance, its LoRA tuning can achieve training speeds that are up to 3.7 times quicker, along with better Rouge scores in generating advertising text compared to traditional methods. Crafted with adaptability at its core, LLaMA-Factory's framework accommodates a wide range of model types and configurations. Users can easily incorporate their datasets and leverage the platform's tools for enhanced fine-tuning results. Detailed documentation and numerous examples are provided to help users navigate the fine-tuning process confidently. In addition to these features, the platform fosters collaboration and the exchange of techniques within the community, promoting an atmosphere of ongoing enhancement and innovation. Ultimately, LLaMA-Factory empowers users to push the boundaries of what is possible with model fine-tuning.

Media

Media

Integrations Supported

GPT-5.4 nano
Gemini 2.0 Flash-Lite

Integrations Supported

ChatGLM
DeepSeek
Gemma
LLaVA
Llama
Llama 3
MLflow
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
OpenAI
PaliGemma 2
Phi-2
Qwen
TensorBoard
TensorWave
Yi-Large

API Availability

Has API

API Availability

Pricing Information

$0.04 per 1M tokens
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

distil labs

Date Founded

2024

Company Location

Germany

Company Website

www.distillabs.ai/

Company Facts

Organization Name

hoshi-hiyouga

Company Website

github.com/hiyouga/LLaMA-Factory

Categories and Features

Small Language Models

Not specified

Categories and Features

AI Fine-Tuning

Not specified

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