Ferret Description

An advanced End-to-End MLLM is designed to accept various forms of references and effectively ground responses. The Ferret Model utilizes a combination of Hybrid Region Representation and a Spatial-aware Visual Sampler, which allows for detailed and flexible referring and grounding capabilities within the MLLM framework. The GRIT Dataset, comprising approximately 1.1 million entries, serves as a large-scale and hierarchical dataset specifically crafted for robust instruction tuning in the ground-and-refer category. Additionally, the Ferret-Bench is a comprehensive multimodal evaluation benchmark that simultaneously assesses referring, grounding, semantics, knowledge, and reasoning, ensuring a well-rounded evaluation of the model's capabilities. This intricate setup aims to enhance the interaction between language and visual data, paving the way for more intuitive AI systems.

Pricing

Pricing Starts At:
Free
Pricing Information:
Open source
Free Version:
Yes

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Company Details

Company:
Apple
Year Founded:
1976
Headquarters:
United States
Website:
github.com/apple/ml-ferret

Media

Ferret Screenshot 1
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Product Details

Platforms
Web-Based
Types of Training
Training Docs

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