Nous-Hermes-2-Vision-Alpha
Maintainer: NousResearch
299
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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
Nous-Hermes-2-Vision stands as a pioneering Vision-Language Model, leveraging advancements from the renowned OpenHermes-2.5-Mistral-7B by teknium. This model incorporates two pivotal enhancements, setting it apart as a cutting-edge solution. It harnesses the formidable SigLIP-400M, a more lightweight vision encoder that delivers a remarkable boost in performance. Additionally, the training data includes a unique feature of function calling, transforming Nous-Hermes-2-Vision into a Vision-Language Action Model.
Model inputs and outputs
Nous-Hermes-2-Vision is a multimodal model that takes both image and text inputs, and generates text outputs. The model can be used for a variety of tasks, including image-to-text generation, image-based question answering, and vision-language instruction following.
Inputs
- Images: The model can accept various image formats, such as JPG, PNG, or WebP, as input.
- Text: The model can accept text prompts or instructions as input, which can be used to guide the generation or processing of the input image.
Outputs
- Text: The model generates textual output, such as captions, descriptions, or responses to questions about the input image.
Capabilities
Nous-Hermes-2-Vision excels at tasks that require understanding and reasoning about visual information in conjunction with language. For example, the model can be used to generate detailed captions for images, answer questions about the content of an image, or follow instructions for performing actions based on the visual input.
What can I use it for?
With its versatile capabilities, Nous-Hermes-2-Vision can be applied to a wide range of projects and use cases. Some potential applications include:
- Image captioning: Generate natural language captions for images to assist with accessibility, search, or content organization.
- Visual question answering: Answer questions about the content of an image, such as identifying objects, people, or activities.
- Visual instruction following: Use the model to understand and follow step-by-step visual instructions, such as for assembling products or completing tasks.
- Multimodal content generation: Combine visual and textual inputs to create compelling, contextual content for creative applications or marketing purposes.
Things to try
One interesting aspect of Nous-Hermes-2-Vision is its ability to leverage function calling to enhance its capabilities. By incorporating a custom dataset with function calling, the model can be used to perform specific actions or computations based on the input image and text. For example, you could provide the model with an image of a stock chart and a prompt to "Analyze the stock fundamentals for this company," and the model would generate a detailed response with the relevant financial data.
This function calling capability sets Nous-Hermes-2-Vision apart from traditional vision-language models and opens up a wide range of possibilities for integrating the model into automated workflows or decision-support systems.
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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