Product Information
What is Apple ferret?
End-to-end MLLM, accepting any form of response and foundation.
Key Contributions:
Ferret Model - Hybrid region representation + spatially aware visual sampler enables fine-grained and open-ended photographic roles and grounding in MLLM.
GRIT Dataset (~1.1M) - A large-scale, hierarchical, robust grounding and prompt instruction-tuning dataset.
Ferret-Bench - A multimodal evaluation benchmark that collectively requires referencing/grounding, semantics, knowledge, and reasoning.
Usage and License Statement: Data and code are for research use and licensing only. They are also restricted to uses compliant with the licensing agreements of Llama, Vicuna, and GPT-4. The dataset is licensed under CC BY-NC 4.0 (non-commercial use only), and models trained on this dataset should not be used beyond research purposes.
How to use Apple ferret?
Apple Ferret is an end-to-end multimodal large language model (MLLM) capable of accepting any form of reference and performing responsive localization, with its core value lying in achieving fine-grained, open-vocabulary referencing and localization capabilities.
Core Functions of Apple ferret
Image recognition
AI-Driven
AI writing
AI-Powered
AI Writing
Usage Scenarios of Apple ferret
- Conduct fine-grained, open-vocabulary referring and grounding research
- Build and evaluate multimodal evaluation benchmarks involving reference, grounding, semantics, knowledge, and reasoning
- Multimodal large language model for research purposes
- Using its datasets and models in non-commercial research projects.
Common Questions about Apple ferret
What does Apple Ferret do?
How do I use Apple Ferret?
What are the core features of Apple Ferret?
What are the use cases for Apple Ferret?
