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While the extent and nature of the biases of the DALL\u00b7E mini model have yet to be fully documented, given the fact that the model was trained on unfiltered data from the Internet, it may generate images that contain stereotypes against minority groups. Work to analyze the nature and extent of these limitations is ongoing, and will be documented in more detail in the <a href=\"https://huggingface.co/dalle-mini/dalle-mini\" target=\"_blank\">DALL\u00b7E mini model card</a>.\n</p>\n</details>", "name": "markdown", "visible": true, "style": {}}}, {"id": 13, "type": "markdown", "props": {"value": "<p style='text-align: center'>\nDALL\u00b7E mini is migrating to \ud83d\udd8d\ufe0f <a href=\"https://www.craiyon.com/\" target=\"_blank\">craiyon.com</a>\n</p>", "name": "markdown", "visible": true, "style": {}}}, {"id": 14, "type": "markdown", "props": {"value": "<hr />\n<p style='text-align: center'>\nCreated by <a href=\"https://twitter.com/borisdayma\" target=\"_blank\">Boris Dayma</a> et al. 2021-2022\n<br/>\n<a href=\"https://github.com/borisdayma/dalle-mini\" target=\"_blank\">GitHub</a> | <a href=\"https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini-Generate-images-from-any-text-prompt--VmlldzoyMDE4NDAy\" target=\"_blank\">Project Report</a>\n<p style='text-align: center'>Powered by Google <a href=\"https://sites.research.google/trc/\" target=\"_blank\">TPU Research Cloud</a>\n</p>", "name": "markdown", "visible": true, "style": {}}}], "theme": "default", "css": ".container { max-width: 800px; margin: auto; }", "title": "Gradio", "enable_queue": false, "layout": {"id": 0, "children": [{"id": 1, "children": [{"id": 2}, {"id": 3}, {"id": 4, "children": [{"id": 5, "children": [{"id": 6, "children": [{"id": 7}, {"id": 8}]}]}, {"id": 9}]}]}, {"id": 10, "children": [{"id": 11}, {"id": 12}, {"id": 13}, {"id": 14}]}]}, "dependencies": [{"targets": [8], "trigger": "click", "inputs": [7], "outputs": [9], "backend_fn": false, "js": "\n async (text) => {\n try {\n document.querySelector('#screenshot').style.display = 'none';\n response = await fetch('https://bf.dallemini.ai/generate', {\n method: 'POST',\n headers: {\n 'Accept': 'application/json',\n 'Content-Type': 'application/json'\n },\n body: JSON.stringify({\n prompt: text\n })\n });\n response = await response.json()\n let imgs = response.images.map(r => \"data:image/png;base64,\" + r)\n document.querySelector('#screenshot').style.display = 'block';\n return imgs\n } catch (e) {\n alert(\"Too much traffic, please try again.\")\n IMG = \"data:image/png;base64,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\"\n document.querySelector('#screenshot').style.display = 'block';\n return Array(9).fill(IMG)\n }\n }\n ", "status_tracker": null, "queue": null, "api_name": null, "scroll_to_output": false, "show_progress": true}, {"targets": [11], "trigger": "click", "inputs": [], "outputs": [], "backend_fn": false, "js": "\n () => {\n const captureElement = document.getElementById(1)\n let bg_color = getComputedStyle(document.querySelector(\"#root .container\"))[\"background-color\"]\n captureElement.style.backgroundColor = bg_color; \n html2canvas(captureElement)\n .then(canvas => {\n canvas.style.display = 'none'\n document.body.appendChild(canvas)\n return canvas\n })\n .then(canvas => {\n const image = canvas.toDataURL('image/png').replace('image/png', 'image/octet-stream')\n const a = document.createElement('a')\n const date = new Date()\n const filename = `dallemini_${date.getFullYear()}-${date.getMonth() + 1}-${date.getDate()}_${date.getHours()}-${date.getMinutes()}-${date.getSeconds()}.png`\n a.setAttribute('download', filename)\n a.setAttribute('href', image)\n a.click()\n canvas.remove()\n })\n }\n ", "status_tracker": null, "queue": null, "api_name": null, "scroll_to_output": false, "show_progress": true}]};
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