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Llava 13b


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The llava-13b model is a text-to-text AI model designed to interpret and generate responses based on visual instructions. With a GPT-4 level capability, the model uses an image URL as input along with a prompt question, then uses its large-scale language and vision processing capabilities to generate a detailed, relevant response. The model's output is an informative statement based on the image and prompt, providing useful insights and details about the queried scenario.

Use cases

The llava-13b AI model offers a unique blend of visual and language interpretation abilities that could be applied to a variety of tasks. Possible use cases for this text-to-text model could primarily be in visual assistance, information identification, object detection, and safety awareness. For instance, it could be incorporated into an interactive travel guide application, offering users location-specific recommendations and providing answers to user queries like "Is it safe to swim here?" based on pictures of the location. Another use case could be in the education sector, where the model could be used to create interactive visual studying tools that offer descriptions and explanations of visual content. Other potential applications could include navigation assistance for visually impaired individuals and remote safety evaluations, where users could receive real-time, image-based advice on possible hazards or regulations. In areas such as law enforcement or insurance investigations, the model may provide assistance in case investigations by interpreting images or scenes and providing detailed descriptions. It's a tool that could also play a significant role in industrial environments where inspectors need to monitor sites remotely.



Cost per run
Avg run time

Creator Models

Temporalnet Sdxl$?117
Llava V1.6 Vicuna 13b$?175,659
Jina Embeddings V2 Base En$?38
Jina Embeddings V2 Small En$?32
Llava V1.6 34b$?223,157

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Summary of this model and related resources.

Model NameLlava 13b

Visual instruction tuning towards large language and vision models with GPT...

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Paper LinkView on Arxiv


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