llava-v1.6-mistral-7b-hf
Maintainer: llava-hf
132
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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 llava-v1.6-mistral-7b-hf model is a multimodal chatbot AI model developed by the llava-hf team. It builds upon the previous LLaVA-1.5 model by using the Mistral-7B language model as its base and training on a more diverse and higher-quality dataset. This allows for improved OCR, common sense reasoning, and overall performance compared to the previous version.
The model combines a pre-trained large language model with a pre-trained vision encoder, enabling it to handle multimodal tasks like image captioning, visual question answering, and multimodal chatbots. It is an evolution of the LLaVA-1.5 model, with enhancements such as increased input image resolution and improved visual instruction tuning.
Similar models include the nanoLLaVA, a sub-1B vision-language model designed for efficient edge deployment, and the llava-v1.6-34b which uses the larger Nous-Hermes-2-34B language model.
Model inputs and outputs
Inputs
- Image: The model can accept images as input, which it then processes and combines with the text prompt to generate a response.
- Text prompt: The text prompt should follow the format
[INST] <image>\nWhat is shown in this image? [/INST]and describe the desired task, such as image captioning or visual question answering.
Outputs
- Text response: The model generates a text response based on the input image and text prompt, providing a description, answer, or other relevant information.
Capabilities
The llava-v1.6-mistral-7b-hf model has enhanced capabilities compared to its predecessor, LLaVA-1.5, due to the use of the Mistral-7B language model and improved training data. It can more accurately perform tasks like image captioning, visual question answering, and multimodal chatbots, leveraging its improved OCR and common sense reasoning abilities.
What can I use it for?
You can use the llava-v1.6-mistral-7b-hf model for a variety of multimodal tasks, such as:
- Image captioning: Generate natural language descriptions of images.
- Visual question answering: Answer questions about the contents of an image.
- Multimodal chatbots: Build conversational AI assistants that can understand and respond to both text and images.
The model's performance on these tasks makes it a useful tool for applications in areas like e-commerce, education, and customer service.
Things to try
One interesting aspect of the llava-v1.6-mistral-7b-hf model is its ability to handle diverse and high-quality data, which has led to improvements in its OCR and common sense reasoning capabilities. You could try using the model to caption images of complex scenes, or to answer questions that require understanding the broader context of an image rather than just its contents.
Additionally, the model's use of the Mistral-7B language model, which has better commercial licenses and bilingual support, could make it a more attractive option for commercial applications compared to the previous LLaVA-1.5 model.
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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