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# KahabMiniGenT2Im: Lightweight Stable Diffusion Model for Text-to-Image Generation
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**Description**: KahabMiniGenT2Im is a lightweight Stable Diffusion model developed by Mohammed Kahab K, an ML engineer, for generating high-quality 256x256 images from text prompts. Trained on a small dataset, this tiny model is optimized for efficiency, making it suitable for low-resource environments like Google Colab or consumer GPUs. Leveraging a custom `UNetConditional` architecture, it provides effective text-to-image generation with minimal computational requirements.
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---
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license: mit
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language:
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- en
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new_version: KAHABKALU/KahabMiniGenT2Im
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pipeline_tag: text-to-image
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library_name: diffusers
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tags:
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- '#StableDiffusion'
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- '#TextToImage'
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- '#MachineLearning'
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- '#ImageGeneration'
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- '#LightweightModel'
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- '#UNet'
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- '#DiffusionModel'
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- '#HuggingFace'
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- '#TextToImageGeneration'
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- '#MLModel'
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---
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# KahabMiniGenT2Im: Lightweight Stable Diffusion Model for Text-to-Image Generation
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**Description**: KahabMiniGenT2Im is a lightweight Stable Diffusion model developed by Mohammed Kahab K, an ML engineer, for generating high-quality 256x256 images from text prompts. Trained on a small dataset, this tiny model is optimized for efficiency, making it suitable for low-resource environments like Google Colab or consumer GPUs. Leveraging a custom `UNetConditional` architecture, it provides effective text-to-image generation with minimal computational requirements.
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