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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Cleanlab Studio offers a comprehensive solution for managing data quality and executing data-centric AI processes within a unified framework designed for both analytics and machine learning endeavors. Its automated pipeline simplifies the machine learning workflow by handling essential tasks such as data preprocessing, fine-tuning foundation models, optimizing hyperparameters, and selecting the best models for your needs. Utilizing machine learning models, it identifies data-related problems, allowing you to retrain on your refined dataset with a single click. You can view a complete heatmap that illustrates recommended corrections for every class in your dataset. All this valuable information is accessible for free as soon as you upload your data. Additionally, Cleanlab Studio comes equipped with a variety of demo datasets and projects, enabling you to explore these examples in your account right after logging in. Moreover, this user-friendly platform makes it easy for anyone to enhance their data management skills and improve their machine learning outcomes.

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.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift Yes 
Amazon S3 Yes 
ChatGLM No 
Dropbox Yes 
JupyterHub Yes 
Keras Yes 
LLaVA No 
Llama No 
Llama 3 No 
MLflow No 
Mixtral 8x22B No 
OpenAI No 
Phi-2 No 
Snowflake Yes 
TensorBoard No 
TensorWave No 
Vertica Yes 
Weaviate Yes 
Yi-Large No 
pandas Yes 

Integrations

Amazon Redshift No 
Amazon S3 No 
ChatGLM Yes 
Dropbox No 
JupyterHub No 
Keras No 
LLaVA Yes 
Llama Yes 
Llama 3 Yes 
MLflow Yes 
Mixtral 8x22B Yes 
OpenAI Yes 
Phi-2 Yes 
Snowflake No 
TensorBoard Yes 
TensorWave Yes 
Vertica No 
Weaviate No 
Yi-Large Yes 
pandas No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Cleanlab

Country

United States

Website

cleanlab.ai/

Vendor Details

Company Name

hoshi-hiyouga

Website

github.com/hiyouga/LLaMA-Factory

Product Features

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

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