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Model Card for Amber Hoardz Text-To-3D

Embracing the content generation is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion functions

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Model Details

Model Description

Embracing the content generation

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  • Model type: Language model
  • Language(s) (NLP): en
  • License: pddl
  • Parent Model: More information needed
  • Resources for more information: More information needed

Uses

Direct Use

Downstream Use [Optional]

Out-of-Scope Use

Bias, Risks, and Limitations

Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.

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Training Details

Training Data

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Training Procedure

Preprocessing

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Speeds, Sizes, Times

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Model Examination

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation

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Glossary [optional]

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Model Card Authors [optional]

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How to Get Started with the Model

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