H&A Models
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README.md
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<!-- Provide a quick summary of what the model is/does. -->
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# Model Details
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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## Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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# Uses
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<!-- 3DKX is a model that was trained on highly detailed 3D rendered pictures of various subjects such as landscapes, scenes, models, textures, and more.
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Our aim is to provide a useful tool that can produce consistent and high-resolution renders for creative purposes such as storyboarding, sketching, templates, wallpapers, and more. -->
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[More Information Needed]
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## Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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## Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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# Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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## Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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##
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Use the code below to get started with the model.
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# Training Details
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## Training Data
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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## Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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### Preprocessing [optional]
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[More Information Needed]
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### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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# Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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## Testing Data, Factors & Metrics
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### Testing Data
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<!-- This should link to a Data Card if possible. -->
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[More Information Needed]
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### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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## Results
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### Summary
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# Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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# Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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# Technical Specifications [optional]
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## Model Architecture and Objective
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<!-- Provide a quick summary of what the model is/does. -->
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3DKX V2
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# Model Details
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3DKX V2 is a model that was trained on highly detailed 3D rendered pictures of various subjects such as landscapes, scenes, models, textures, and more.
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Our aim is to provide a useful tool that can produce consistent and high-resolution renders for creative purposes such as storyboarding, sketching, templates, wallpapers, and more.
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- **Created By:** [Unvail ai]
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- **Language(s) (NLP):** [English]
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- **License:** [creativeml-openrail-m]
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- **Finetuned from model [SimpMaker 3k3]
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# Uses
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<!-- 3DKX is a model that was trained on highly detailed 3D rendered pictures of various subjects such as landscapes, scenes, models, textures, and more.
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Our aim is to provide a useful tool that can produce consistent and high-resolution renders for creative purposes such as storyboarding, sketching, templates, wallpapers, and more. -->
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• 3D renders, cartoony or realistic
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• Landscapes
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• Scenery
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• Fantasy, creatures, RPG renders
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• Portraits
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• Dramatic scenes, horror, dark, obscure
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## Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## Get started with the model, use our cheat sheet !
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Use the code below to get started with the model.
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# Training Details
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## Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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## Results
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### Summary
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# Technical Specifications [optional]
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## Model Architecture and Objective
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