Phi-3.5-vision-instruct
Maintainer: microsoft
463
⚙️
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
Create account to get full access
Model overview
The Phi-3.5-vision-instruct is a lightweight, state-of-the-art open multimodal model built upon datasets which include synthetic data and filtered publicly available websites, with a focus on very high-quality, reasoning-dense data both on text and vision. It belongs to the Phi-3 model family, and the multimodal version can support a 128K context length. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures.
Model inputs and outputs
Inputs
- Text: The model can take text input using a chat format.
- Images: The model can process single images or multiple images/video frames for tasks like image comparison and multi-image/video summarization.
Outputs
- Generated text: The model generates relevant text in response to the input prompt.
Capabilities
The Phi-3.5-vision-instruct model provides capabilities for general purpose AI systems and applications with visual and text input requirements. Key use cases include memory/compute constrained environments, latency-bound scenarios, general image understanding, optical character recognition, chart and table understanding, multiple image comparison, and multi-image or video clip summarization.
What can I use it for?
The Phi-3.5-vision-instruct model is intended for broad commercial and research use in English. It can be used as a building block for generative AI powered features, accelerating research on language and multimodal models. Some potential use cases include:
- Developing AI assistants with visual understanding capabilities
- Automating document processing tasks like extracting insights from charts and tables
- Enabling multi-modal interfaces for product search and recommendation systems
Things to try
The Phi-3.5-vision-instruct model's multi-frame image understanding and reasoning capabilities allow for interesting applications like detailed image comparison, multi-image summarization, and optical character recognition. Developers could explore leveraging these abilities to build novel AI-powered features for their products and services.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
🔮
Phi-3-vision-128k-instruct
741
Phi-3-vision-128k-instruct is a lightweight, state-of-the-art open multimodal model built upon datasets which include synthetic data and filtered publicly available websites, with a focus on very high-quality, reasoning dense data both on text and vision. The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures. Similar models in the Phi-3 family include the Phi-3-mini-128k-instruct and Phi-3-mini-4k-instruct. These models have fewer parameters (3.8B) compared to the full Phi-3-vision-128k-instruct but share the same training approach and underlying architecture. Model inputs and outputs Inputs Text**: The model accepts text input, and is best suited for prompts using a chat format. Images**: The model can process visual inputs in addition to text. Outputs Generated text**: The model generates text in response to the input, aiming to provide safe, ethical and accurate information. Capabilities The Phi-3-vision-128k-instruct model is designed for broad commercial and research use, with capabilities that include general image understanding, OCR, and chart and table understanding. It can be used to accelerate research on efficient language and multimodal models, and as a building block for generative AI powered features. What can I use it for? The Phi-3-vision-128k-instruct model is well-suited for applications that require memory/compute constrained environments, latency bound scenarios, or general image and text understanding. Example use cases include: Visual question answering**: Given an image and a text question about the image, the model can generate a relevant response. Image captioning**: The model can generate captions describing the contents of an image. Multimodal task automation**: Combining text and image inputs, the model can be used to automate tasks like form filling, document processing, or data extraction. Things to try To get a sense of the model's capabilities, you can try prompting it with a variety of multimodal tasks, such as: Asking it to describe the contents of an image in detail Posing questions about the objects, people, or activities depicted in an image Requesting the model to summarize the key information from a document containing both text and figures/tables Asking it to generate steps for a visual instruction manual or recipe The model's robust reasoning abilities, combined with its understanding of both text and vision, make it a powerful tool for tackling a wide range of multimodal challenges.
Updated Invalid Date
🤿
Phi-3-medium-128k-instruct
295
The Phi-3-medium-128k-instruct is a 14B parameter, lightweight, state-of-the-art open model developed by Microsoft. It was trained on synthetic data and filtered publicly available websites, with a focus on high-quality and reasoning-dense properties. The model belongs to the Phi-3 family, which also includes Phi-3-mini-128k-instruct and Phi-3-mini-4k-instruct, differing in parameter size and context length. The model underwent a post-training process that incorporated supervised fine-tuning and direct preference optimization to enhance its instruction following and safety. When evaluated on benchmarks testing common sense, language understanding, math, code, long context, and logical reasoning, the Phi-3-medium-128k-instruct demonstrated robust and state-of-the-art performance among models of similar and larger sizes. Model inputs and outputs Inputs Text**: The Phi-3-medium-128k-instruct model is best suited for text-based prompts, particularly those using a chat format. Outputs Generated text**: The model generates relevant and coherent text in response to the input prompt. Capabilities The Phi-3-medium-128k-instruct model showcases strong reasoning abilities across a variety of domains, including common sense, language understanding, mathematics, coding, and logical reasoning. For example, it can provide step-by-step solutions to math problems, generate code to implement algorithms, and engage in multi-turn conversations to demonstrate its understanding of complex topics. What can I use it for? The Phi-3-medium-128k-instruct model is intended for broad commercial and research use cases that require memory/compute-constrained environments, latency-bound scenarios, and strong reasoning capabilities. It can be used as a building block for developing generative AI-powered features, such as question-answering systems, code generation tools, and educational applications. Things to try One interesting aspect of the Phi-3-medium-128k-instruct model is its ability to handle long-form context. Try providing the model with a multi-paragraph prompt and see how it maintains coherence and relevance in its generated response. You can also experiment with using the model for specific tasks, such as translating technical jargon into plain language or generating step-by-step explanations for complex concepts.
Updated Invalid Date
🐍
Phi-3.5-MoE-instruct
473
The Phi-3.5-MoE-instruct is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available documents - with a focus on very high-quality, reasoning dense data. The model supports multilingual and comes with 128K context length (in tokens). The model underwent a rigorous enhancement process, incorporating supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures. The Phi-3.5-MoE-instruct model is part of the Phi-3 model family, which also includes the Phi-3.5-mini-instruct and Phi-3.5-vision-instruct models. Model inputs and outputs Inputs Text**: The model is best suited for prompts using the chat format. Outputs Generated text**: The model generates text in response to the input. Capabilities The Phi-3.5-MoE-instruct model is designed for strong reasoning, especially in areas like code, math, and logic. It performs well in memory/compute constrained environments and latency bound scenarios. What can I use it for? The Phi-3.5-MoE-instruct model is intended for commercial and research use in multiple languages. It can be used as a building block for general purpose AI systems and applications that require memory/compute constrained environments, latency bound scenarios, and strong reasoning capabilities. Things to try You can try the Phi-3.5-MoE-instruct model using the Try It link provided. This allows you to interactively experiment with the model and see its capabilities in action.
Updated Invalid Date
🔮
Phi-3-medium-4k-instruct
135
The Phi-3-medium-4k-instruct is a 14B parameter, lightweight, state-of-the-art open model trained by Microsoft. It is part of the Phi-3 family of models which come in different sizes and context lengths, including the Phi-3-medium-128k-instruct variant with 128k context length. The Phi-3 models have undergone a post-training process that incorporates both supervised fine-tuning and direct preference optimization to enhance their instruction following capabilities and safety measures. When evaluated on benchmarks testing common sense, language understanding, math, code, long context, and logical reasoning, the Phi-3-medium-4k-instruct demonstrated robust and state-of-the-art performance compared to models of similar and larger size. Model inputs and outputs Inputs Text**: The model is best suited for text-based prompts, particularly in a conversational "chat" format. Outputs Generated text**: The model outputs generated text in response to the input prompt. Capabilities The Phi-3-medium-4k-instruct model showcases strong reasoning and language understanding capabilities, particularly in areas like code, math, and logical reasoning. It can be a useful tool for building general-purpose AI systems and applications that require memory/compute-constrained environments, latency-bound scenarios, or advanced reasoning. What can I use it for? The Phi-3-medium-4k-instruct model can be leveraged for a variety of commercial and research use cases in English, such as powering AI assistants, generating content, and accelerating language model research. Its compact size and strong performance make it well-suited for applications with limited resources or low-latency requirements. Things to try One interesting aspect of the Phi-3 models is their focus on safety and alignment with human preferences. You could experiment with the model's ability to follow instructions and generate content that adheres to ethical guidelines. Additionally, its strong performance on code and math-related tasks suggests it could be a useful tool for building AI-powered programming and educational applications.
Updated Invalid Date