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--- |
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tags: |
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- image-generation |
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- generative-model |
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- multimodal |
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- SOTA |
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model_name: CustomImageGenerator |
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model_type: image-generation |
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description: > |
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CustomImageGenerator is a state-of-the-art multimodal generative model based |
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on the GPT-2 architecture, capable of generating high-quality images from |
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textual prompts. The model combines advanced techniques from natural language |
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processing (NLP) and computer vision to produce visually coherent and |
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contextually relevant images. |
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architecture: GPT-2 |
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tasks: |
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- image-generation |
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references: |
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- title: Generative Pre-trained Transformer 2.0 |
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url: > |
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https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf |
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- title: Learning to Generate Images from Text |
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url: https://arxiv.org/abs/1511.02793 |
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- title: Stable Diffusion Models for Image Generation |
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url: https://arxiv.org/abs/2105.05233 |
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related_models: |
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- name: BigGAN |
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description: State-of-the-art generative adversarial network (GAN) for image generation. |
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url: https://github.com/ajbrock/BigGAN-PyTorch |
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- name: CLIP |
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description: > |
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Contrastive Language-Image Pre-training model for understanding images and |
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text. |
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url: https://github.com/openai/CLIP |
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language: |
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- en |
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license: apache-2.0 |
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--- |
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animation: fadeIn 1s ease-in-out; |
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font-weight: 600; |
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text-align: center; |
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transition: background 0.3s ease, transform 0.3s ease; |
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background: #0056b3; |
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transform: translateY(-2px); |
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.widget-container { |
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background: rgba(255, 255, 255, 0.05); |
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border-radius: 10px; |
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padding: 20px; |
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margin-top: 40px; |
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animation: fadeIn 1s ease-in-out; |
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position: relative; |
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overflow: hidden; |
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content: ''; |
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left: -50%; |
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background: radial-gradient(circle, rgba(255, 255, 255, 0.1), transparent); |
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animation: rotate 10s infinite linear; |
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text-align: center; |
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font-size: 24px; |
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font-weight: 700; |
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color: #e0e0e0; |
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margin-bottom: 20px; |
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text-shadow: 1px 1px 3px rgba(0, 0, 0, 0.5); |
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display: flex; |
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padding: 40px; |
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border-radius: 20px; |
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cursor: pointer; |
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transition: transform 0.3s ease; |
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margin: 20px auto; |
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max-width: 600px; |
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transform: translateY(-5px); |
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font-size: 36px; |
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margin-bottom: 20px; |
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color: #333; |
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</style> |
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<div class="container"> |
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<div class="section"> |
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<div class="section-header"> |
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<h2 class="section-title">🎨 Use Cases</h2> |
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</div> |
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<div class="section-content"> |
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<div class="section-description"> |
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<p><strong>🖼️ Artistic Content Generation</strong></p> |
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<p>CustomImageGenerator serves as a virtual canvas for artists and designers, enabling the creation of captivating artworks from mere text. Whether it's envisioning mythical landscapes or crafting futuristic cityscapes, the model ignites creativity and opens doors to boundless artistic exploration.</p> |
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</div> |
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</div> |
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</div> |
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<div class="section"> |
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<div class="section-header"> |
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<h2 class="section-title">ℹ️ Model Details</h2> |
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</div> |
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<div class="section-content"> |
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<div class="section-description"> |
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<p><strong>🧠 Architecture</strong></p> |
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<p>CustomImageGenerator is built upon the GPT-2 architecture, a powerful transformer-based model renowned for its natural language processing capabilities. Leveraging GPT-2's architecture, the model seamlessly integrates text and image generation, offering a holistic approach to multimodal AI.</p> |
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</div> |
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</div> |
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</div> |
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<div class="section"> |
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<div class="section-header"> |
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<h2 class="section-title">🌟 Significance</h2> |
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</div> |
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<div class="section-content"> |
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<div class="section-description"> |
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<p>CustomImageGenerator represents a paradigm shift in multimodal AI, bridging the gap between language and vision to enable seamless communication and creativity. Its ability to generate contextually relevant images from textual prompts opens up new possibilities for artistic expression, conceptualization, and product design, ushering in a new era of human-machine collaboration and innovation.</p> |
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</div> |
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</div> |
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</div> |
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</div> |
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