vila-7b
Maintainer: adirik
2
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
vila-7b is a multi-image visual language model developed by Replicate creator adirik. It is a smaller version of the larger VILA model, which was pretrained on interleaved image-text data. The vila-7b model can be used for tasks like image captioning, visual question answering, and multimodal reasoning. It is similar to other multimodal models like stylemc, realistic-vision-v6.0, and kosmos-g also created by adirik.
Model inputs and outputs
The vila-7b model takes an image and a text prompt as input, and generates a textual response based on the prompt and the content of the image. The input image can be used to provide additional context and grounding for the generated text.
Inputs
- image: The image to discuss
- prompt: The query to generate a response for
- top_p: When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens
- temperature: When decoding text, higher values make the model more creative
- num_beams: Number of beams to use when decoding text; higher values are slower but more accurate
- max_tokens: Maximum number of tokens to generate
Outputs
- Output: The model's generated response to the provided prompt and image
Capabilities
The vila-7b model can be used for a variety of multimodal tasks, such as image captioning, visual question answering, and multimodal reasoning. It can generate relevant and coherent responses to prompts about images, drawing on the visual information to provide informative and contextual outputs.
What can I use it for?
The vila-7b model could be useful for applications that require understanding and generating text based on visual input, such as automated image description generation, visual-based question answering, or even as a component in larger multimodal systems. Companies in industries like media, advertising, or e-commerce could potentially leverage the model's capabilities to automate image-based content generation or enhance their existing visual-text applications.
Things to try
One interesting thing to try with the vila-7b model is to provide it with a diverse set of images and prompts that require it to draw connections between the visual and textual information. For example, you could ask the model to compare and contrast two different images, or to generate a story based on a series of images. This could help explore the model's ability to truly understand and reason about the relationships between images and text.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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