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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.

What is Intel Tiber AI Cloud?

The Intel® Tiber™ AI Cloud is a powerful platform designed to effectively scale artificial intelligence tasks by leveraging advanced computing technologies. It incorporates specialized AI hardware, featuring products like the Intel Gaudi AI Processor and Max Series GPUs, which optimize model training, inference, and deployment processes. This cloud solution is specifically crafted for enterprise applications, enabling developers to build and enhance their models utilizing popular libraries such as PyTorch. Furthermore, it offers a range of deployment options and secure private cloud solutions, along with expert support, ensuring seamless integration and swift deployment that significantly improves model performance. By providing such a comprehensive package, Intel Tiber™ empowers organizations to fully exploit the capabilities of AI technologies and remain competitive in an evolving digital landscape. Ultimately, it stands as an essential resource for businesses aiming to drive innovation and efficiency through artificial intelligence.

Media

Media

Integrations Supported

Arm DDT
BeyondTrust Cloud Privilege Broker
ChatGLM
DeepSeek R1
HP Advance
Intel Tiber AI Studio
Jupyter Notebook
JupyterLab
LLaVA
Llama
Llama 3
Mistral AI
Mixtral 8x22B
OpenAI
PaliGemma 2
Phi-2
PyTorch
Qwen
TensorBoard
Yi-Large

Integrations Supported

Arm DDT
BeyondTrust Cloud Privilege Broker
ChatGLM
DeepSeek R1
HP Advance
Intel Tiber AI Studio
Jupyter Notebook
JupyterLab
LLaVA
Llama
Llama 3
Mistral AI
Mixtral 8x22B
OpenAI
PaliGemma 2
Phi-2
PyTorch
Qwen
TensorBoard
Yi-Large

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

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

hoshi-hiyouga

Company Website

github.com/hiyouga/LLaMA-Factory

Company Facts

Organization Name

Intel

Date Founded

1968

Company Location

United States

Company Website

ai.cloud.intel.com

Categories and Features

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

HPC

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