LLaVA-13b-delta-v0
Maintainer: liuhaotian
223
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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-13b-delta-v0 model is an open-source chatbot trained by fine-tuning the LLaMA language model and Vicuna on GPT-generated multimodal instruction-following data. It is an autoregressive language model based on the transformer architecture. The model was developed by liuhaotian, who has also created similar models such as llava-v1.6-mistral-7b and llava-med-7b-delta.
Model Inputs and Outputs
The LLaVA-13b-delta-v0 model is a language model that can generate human-like text given a prompt. It also has multimodal capabilities, allowing it to generate text based on both textual and visual inputs.
Inputs
- Text prompts: The model can accept text prompts to generate relevant responses.
- Images: The model can also accept images as part of the input, allowing it to generate text describing or relating to the provided image.
Outputs
- Textual responses: The primary output of the model is human-like textual responses to the provided prompts or image-text combinations.
Capabilities
The LLaVA-13b-delta-v0 model has been trained to engage in open-ended conversation, answer questions, and describe images. It demonstrates strong language understanding and generation capabilities, as well as the ability to reason about and describe visual information. The model can be particularly useful for research on large multimodal models and chatbots.
What Can I Use It For?
The primary intended use of the LLaVA-13b-delta-v0 model is for research on large multimodal models and chatbots. Researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence may find this model useful for exploring various multimodal applications and advancing the state of the art in these fields.
Things to Try
Some interesting things to try with the LLaVA-13b-delta-v0 model include:
- Evaluating the model's ability to understand and describe complex visual scenes by providing it with a diverse set of images.
- Exploring the model's language understanding and generation capabilities by engaging it in open-ended conversations on a variety of topics.
- Investigating the model's reasoning abilities by asking it to answer questions that require combining information from both text and visual inputs.
- Experimenting with different prompting strategies to see how the model's responses can be tailored for specific use cases or applications.
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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