Zero Shot Image To Text
Some possible use cases for this AI model include image captioning, automatic transcription of images for accessibility purposes, and content generation for social media. For image captioning, the model can be used to automatically generate descriptive text for images in order to enhance the understanding and accessibility of visual content. This could be particularly useful in applications such as image search engines or for assisting visually impaired individuals. Additionally, the model could be used to automatically transcribe text contained within images, helping to make visual content more accessible to individuals who are unable to read or have difficulty reading text. Another potential use case is content generation for social media. The model could be used to automatically generate descriptive captions for images, saving time and effort for social media managers and influencers. The applications for this zero-shot image-to-text model are vast, and with further development and refinement, it has the potential to revolutionize the way we interact with and understand visual content.
- Cost per run
- Avg run time
- Nvidia T4 GPU
You can use this area to play around with demo applications that incorporate the Zero Shot Image To Text model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Currently, there are no demos available for this model.
Summary of this model and related resources.
|Model Name||Zero Shot Image To Text|
image to text generation
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||View on Github|
|Paper Link||View on Arxiv|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$-|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||-|