Pixart-Sigma-600M-Aurel-Manea

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This is a finetune of PixArt-Sigma-XL-2-1024-MS with a dataset comprise of a selection of Aurel Manea's work combined with my own pictures. It is essentially made for making landscapes with unique and dramatic lighting.

Model Details

Model Description

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PixArt-Sigma-XL-2-1024-MS is a lightweight 600M parameters model that can easily run on consumer hardware. I choose this as a base model because it has a good prompt adherence, a 1024 resolution and simply because I could fit a decently large batch size on 24gb of VRAM. My finetune aims at making a decent model to generate nice landscapes in the style of Aurel Manea's work who generously provided his pictures, free of charge, to the world to use. From one of his reddit post, he specifically said that he would enjoy that people use his work in training an AI.

• Developed by: [me]
• Funded by [my wife]: [for paying the electricity bill]
• Shared by [me]: [??]
• Model type: [DiT]
• Language(s) (NLP): [English]
• License: [apache-2.0]
• Finetuned from model [PixArt-Sigma-XL-2-1024-MS]: [Thanks to their team for making this model available to the community]

Model Sources [optional]

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• Repository: [https://huggingface.co/PixArt-alpha/PixArt-Sigma-XL-2-1024-MS]

Uses

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Comfy-UI works well.

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

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [BF16] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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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

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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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Software

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Citation [optional]

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Glossary [optional]

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