MiniCPM-Llama3-V-2_5-int4
Maintainer: openbmb
51
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| Property | Value |
|---|---|
| Model Link | View on HuggingFace |
| API Spec | View on HuggingFace |
| Github Link | No Github link provided |
| Paper Link | No paper link provided |
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Model overview
The MiniCPM-Llama3-V-2_5-int4 is an int4 quantized version of the MiniCPM-Llama3-V 2.5 model, developed by openbmb. This means the model has been compressed to use less GPU memory, approximately 9GB, while maintaining performance. It is an image-to-text model capable of generating text descriptions for images.
Model inputs and outputs
The MiniCPM-Llama3-V-2_5-int4 model takes two main inputs: an image and a set of conversational messages. The image is used as the visual context, while the messages provide textual context for the model to generate a relevant response.
Inputs
- Image: The model accepts an image in RGB format, which is used to provide visual information for the task.
- Messages: A list of conversational messages in the format
{'role': 'user', 'content': 'message text'}. These messages give the model additional context to generate an appropriate response.
Outputs
- Generated text: The model outputs a text response that describes the content of the input image, based on the provided conversational context.
Capabilities
The MiniCPM-Llama3-V-2_5-int4 model is capable of generating text descriptions for images, leveraging both the visual information and the conversational context. This can be useful for tasks like image captioning, visual question answering, and interactive image-based dialogues.
What can I use it for?
The MiniCPM-Llama3-V-2_5-int4 model can be used in a variety of applications that involve generating text descriptions for images, such as:
- Image captioning: Automatically generating captions for images to aid in accessibility or for search and retrieval purposes.
- Visual question answering: Answering questions about the contents of an image by generating relevant text responses.
- Interactive image-based dialogues: Building conversational interfaces that can discuss and describe images in a natural way.
Things to try
One interesting aspect of the MiniCPM-Llama3-V-2_5-int4 model is its ability to generate text responses while considering both the visual and conversational context. You could try providing the model with a variety of image-message pairs to see how it responds, and observe how the generated text changes based on the provided context.
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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