Model Type | |
Use Cases |
Areas: | Research, Commercial applications |
|
Applications: | Image captioning, Object detection, Segmentation, Vision-language tasks |
|
Primary Use Cases: | Captioning, Object detection, Segmentation, Vision-language tasks |
|
|
Additional Notes | Used in research and commercial applications without explicit censoring. |
|
Training Details |
Data Sources: | |
Data Volume: | 5.4 billion annotations across 126 million images |
|
Methodology: | Prompt-based approach, sequence-to-sequence architecture |
|
Model Architecture: | Sequence-to-sequence architecture |
|
|
Input Output |
Input Format: | Input format for vision tasks through prompts. |
|
Accepted Modalities: | |
Output Format: | Text-based descriptions and symbols for image annotations. |
|
Performance Tips: | Switch prompts to trigger different tasks. |
|
|