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Eagle-X5-13B

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metadata
license: cc-by-nc-sa-4.0
library_name: transformers
pipeline_tag: text-generation
tags:
  - Eagle
  - VLM

Eagle Model Card

Model details

Model type: Eagle is a family of Vision-Centric High-Resolution Multimodal LLMs. It presents a thorough exploration to strengthen multimodal LLM perception with a mixture of vision encoders and different input resolutions. The model contains a channel-concatenation-based "CLIP+X" fusion for vision experts with different architectures (ViT/ConvNets) and knowledge (detection/segmentation/OCR/SSL). The resulting family of Eagle models support up to over 1K input resolution and obtain strong results on multimodal LLM benchmarks, especially resolution-sensitive tasks such as optical character recognition and document understanding.

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Paper or resources for more information: https://github.com/NVlabs/Eagle

License

  • The code is released under the Apache 2.0 license as found in the LICENSE file.
  • The pretrained weights are released under the CC-BY-NC-SA-4.0 license.
  • The service is a research preview intended for non-commercial use only, and is subject to the following licenses and terms:

Where to send questions or comments about the model: https://github.com/NVlabs/Eagle/issues

Intended use

Primary intended uses: The primary use of Eagle is research on large multimodal models and chatbots.

Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.

Model Architecture:

Architecture Type: Transformer

Input:

Input Type: Image, Text Input Format: Red, Green, Blue;String

Output:

Output Type: Text Output Format: String

[Preferred/Supported] Operating System(s):
Linux

Ethical Considerations

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.