🗺️ map diffuser with text to image 🗺️
Model Details
Model Description
- Developed by: Decision Labs
- Model type: Diffusion Model
- License: CC BY-NC 4.0
- Finetuned from model text2image: https://huggingface.co/docs/diffusers/en/training/text2image
Model Sources [optional]
- Repository: https://huggingface.co/sabman/map-diffuser-v3/
- Paper: Coming Soon
- Demo: https://huggingface.co/spaces/sabman/map-diffuser
Uses
Generates images from a given text prompt. The prompts are in the format:
{style} map of {city} with {features} or
satellite image of {city} with {features} or
satellite image with {features} or
satellite image of {city} with {features} and no {features} and so on…
So for example:
“Satellite image of amsterdam with industrial area and highways”
“Watercolor style map of Amsterdam with residential area and highways”
“Toner style map of Amsterdam with residential area and highways”
“Satellite image with forests and residential, no water”
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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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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Summary
Model Examination [optional]
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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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- Hours used: [More Information Needed]
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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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BibTeX:
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APA:
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