Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

LLaMA-Factory is an innovative open-source platform aimed at simplifying and improving the fine-tuning process for more than 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It accommodates a variety of fine-tuning methods such as Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, empowering users to personalize models with ease. The platform has shown remarkable performance enhancements; for example, its LoRA tuning achieves training speeds that are up to 3.7 times faster along with superior Rouge scores in advertising text generation tasks when compared to conventional techniques. Built with flexibility in mind, LLaMA-Factory's architecture supports an extensive array of model types and configurations. Users can seamlessly integrate their datasets and make use of the platform’s tools for optimized fine-tuning outcomes. Comprehensive documentation and a variety of examples are available to guide users through the fine-tuning process with confidence. Additionally, this platform encourages collaboration and sharing of techniques among the community, fostering an environment of continuous improvement and innovation.

Description

Harness the capabilities of tailored models to gain a strategic edge in your market. With our advanced enterprise Gen AI framework, you can surpass conventional limits and delegate repetitive tasks to robust assistants in real time – the possibilities are endless. For businesses that prioritize data protection, customize and implement generative AI solutions within your own secure cloud environment, ensuring safety and confidentiality at every step.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Llama
Llama 3
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
OpenAI
Amazon Web Services (AWS)
Codestral Mamba
GPT-3.5
Le Chat
Llama 2
Microsoft Dynamics 365
Microsoft SharePoint
Ministral 3B
Mistral Large
Mistral NeMo
Mistral Small
Tune Studio
Vivaticket
Weights & Biases

Integrations

Llama
Llama 3
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
OpenAI
Amazon Web Services (AWS)
Codestral Mamba
GPT-3.5
Le Chat
Llama 2
Microsoft Dynamics 365
Microsoft SharePoint
Ministral 3B
Mistral Large
Mistral NeMo
Mistral Small
Tune Studio
Vivaticket
Weights & Biases

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

hoshi-hiyouga

Website

github.com/hiyouga/LLaMA-Factory

Vendor Details

Company Name

NimbleBox

Founded

2018

Country

United States

Website

tunehq.ai

Product Features

Product 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)

Natural Language Generation

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Alternatives

Alternatives

LM-Kit.NET Reviews

LM-Kit.NET

LM-Kit