Model Overview

Description:

The intfloat/e5-large-unsupervised is a text embedding model without supervised fine-tuning. This is used to generate embeddings from input text. This model is to be used with the Nv IGI SDK embed plugin.

This model is ready for commercial/non-commercial use.

Model Developer: Microsoft

Third-Party Community Consideration

This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see e5-large-unsupervised Model Card.

License/Terms of Use:

This model is distributed under MIT license e5-large-unsupervised License. Please refer to e5-large-unsupervised Model Card. for further details.

Reference(s):

• e5-large-unsupervised Hugging Face

Model Architecture:

• Architecture Type: Transformer
• Network Architecture: MiniLM

Input:

• Input Type(s): Text
• Input Format(s): String
• Input Parameters: 1D

Output:

• Output Type(s): Embedding vectors
• Output Format: Vector
• Output Parameters: 2D

Supported Hardware Microarchitecture Compatibility:

• NVIDIA Ada

Supported Operating System(s):

• Windows

Model Version(s):

• e5-large-unsupervised GGUF q4_k_s 1.0
• Nv IGI SDK Model GUID : {5D458A64-C62E-4A9C-9086-2ADBF6B241C7}

Training, Testing, and Evaluation Datasets:

Training Dataset:

• Data Collection Method by dataset: Unknown
• Labeling Method by dataset: Unknown
• Properties: The model is trained in a contrastive manner with weak supervision signals from Microsoft’s curated large-scale text pair dataset (called CCPairs). Please refer to the e5 training paper for additional information.

Please refer to e5-large-unsupervised Model Card for information on Training, Testing and Evaluation Datasets

Inference:

• Engine: GGUF
• Test Hardware : RTX 4090

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.

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