Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| import os | |
| hf_writer = gr.HuggingFaceDatasetSaver( | |
| os.getenv('HUGGING_FACE_HUB_TOKEN'), | |
| organization="society-ethics", | |
| dataset_name="featured-spaces-submissions", | |
| private=True | |
| ) | |
| principles = [ | |
| { | |
| "title": "🤝 Consentful", | |
| "content": """ | |
| [What is consentful tech?](https://www.consentfultech.io) | |
| Consentful technology supports the self-determination of people who use and are affected by these technologies. | |
| For Spaces, some examples of this can include: | |
| - Demonstrating a commitment to acquiring data from willing, informed, and appropriately compensated sources. | |
| - Designing systems that respect end-user autonomy, e.g. with privacy-preserving techniques. | |
| - Avoiding extractive, chauvinist, ["dark"](https://www.deceptive.design), and otherwise "unethical" patterns of engagement. | |
| Featured Spaces: | |
| - [lvwerra/in-the-stack-gr](https://huggingface.co/spaces/lvwerra/in-the-stack-gr) | |
| - [zama-fhe/encrypted_sentiment_analysis](https://huggingface.co/spaces/zama-fhe/encrypted_sentiment_analysis) | |
| """ | |
| }, | |
| { | |
| "title": "🌎 Sustainable", | |
| "content": """ | |
| These are Spaces that highlight and explore techniques for making machine learning ecologically sustainable. | |
| Examples could include: | |
| - Tracking emissions from training and running inferences on large language models. | |
| - Quantization and distillation methods to reduce carbon footprints without sacrificing model quality. | |
| Featured Space: | |
| - [pytorch/MobileNet_v2](https://huggingface.co/spaces/pytorch/MobileNet_v2) | |
| """ | |
| }, | |
| { | |
| "title": "👁️🗨️ Socially Conscious", | |
| "content": """ | |
| "Socially Conscious" Spaces show us how machine learning can be applied as a force for *good*! | |
| This is quite broad, but some examples could be: | |
| - Using machine learning as part of an effort to tackle climate change. | |
| - Building tools to assist with medical research and practice. | |
| - Developing models for text-to-speech, image captioning, and other tasks aimed at increasing accessibility. | |
| - Creating systems for the digital humanities, such as for Indigenous language revitalization. | |
| Featured Space: | |
| - [vict0rsch/climateGAN](https://huggingface.co/spaces/vict0rsch/climateGAN) | |
| """ | |
| }, | |
| { | |
| "title": "🧑🤝🧑 Inclusive", | |
| "content": """ | |
| These are projects which broaden the scope of who *builds* and *benefits* in the machine learning world. | |
| This could mean things like: | |
| - Curating diverse datasets that increase the representation of underserved groups. | |
| - Training language models on languages that aren't yet available on the Hugging Face Hub. | |
| - Creating no-code frameworks that allow non-technical folk to engage with AI. | |
| Featured Spaces: | |
| - [hackathon-pln-es/Spanish-Nahuatl-Translation](https://huggingface.co/spaces/hackathon-pln-es/Spanish-Nahuatl-Translation) | |
| - [hackathon-pln-es/readability-assessment-spanish](https://huggingface.co/spaces/hackathon-pln-es/readability-assessment-spanish) | |
| """ | |
| }, | |
| { | |
| "title": "✍️ Rigorous", | |
| "content": """ | |
| Among the many concerns that go into creating new models is a seemingly simple question: "Does it work?" | |
| Rigorous projects pay special attention to examining failure cases, protecting privacy through security | |
| measures, and ensuring that potential users (technical and non-technical) are informed of the project's | |
| limitations. | |
| For example: | |
| - Projects built with models that are well-documented with [Model Cards](https://huggingface.co/docs/hub/model-cards). | |
| - Models that are evaluated against cutting-edge benchmarks, with results reported against disaggregated sets. | |
| - Demonstrations of models failing across ["gender, skin type, ethnicity, age or other attributes"](http://gendershades.org/overview.html). | |
| - Techniques for mitigating issues like over-fitting and training data memorization. | |
| Featured Spaces: | |
| - [emilylearning/spurious_correlation_evaluation](https://huggingface.co/spaces/emilylearning/spurious_correlation_evaluation) | |
| - [ml6team/post-processing-summarization](https://huggingface.co/spaces/ml6team/post-processing-summarization) | |
| """ | |
| }, | |
| { | |
| "title": "🤔 Inquisitive", | |
| "content": """ | |
| Some projects take a radical new approach to concepts which may have become commonplace. These projects, often | |
| rooted in critical theory, shine a light on inequities and power structures which challenge the community to | |
| rethink its relationship to technology. | |
| For example: | |
| - [Reframing AI and machine learning from Indigenous perspectives](https://jods.mitpress.mit.edu/pub/lewis-arista-pechawis-kite/release/1). | |
| - [Highlighting LGBTQIA2S+ marginalization in AI](https://edri.org/our-work/computers-are-binary-people-are-not-how-ai-systems-undermine-lgbtq-identity/). | |
| - [Critiquing the harms perpetuated by AI systems](https://www.ajl.org). | |
| Featured Space: | |
| - [society-ethics/Average_diffusion_faces](https://huggingface.co/spaces/society-ethics/Average_diffusion_faces) | |
| """ | |
| }, | |
| ] | |
| def toggle_description(title, content): | |
| with gr.Accordion(label=title, open=False): | |
| gr.Markdown(content, elem_id="margin-top") | |
| def submit_entry(URL, tags, suggestions, comments): | |
| hf_writer.flag( | |
| flag_data=[URL, tags, suggestions, comments] | |
| ) | |
| return [ | |
| gr.Markdown.update( | |
| visible=True, | |
| value="Thank you for your submission! 🤗" | |
| ), | |
| gr.Button.update( | |
| visible=False | |
| ), | |
| gr.Text.update(interactive=False), | |
| gr.Checkboxgroup.update(interactive=False), | |
| gr.Text.update(interactive=False), | |
| gr.TextArea.update(interactive=False), | |
| ] | |
| with gr.Blocks(css="#margin-top {margin-top: 15px} #center {justify-content: space-between;}") as demo: | |
| with gr.Row(elem_id="center"): | |
| with gr.Column(scale=4): | |
| gr.Markdown("## Call for submissions! 📢") | |
| with gr.Column(): | |
| gr.Markdown("<img style='height: 7em;' src='https://huggingface.co/spaces/society-ethics/featured-spaces-submissions/resolve/main/banner.png'/>") | |
| gr.Markdown(""" | |
| Hugging Face is collecting examples of [Spaces](https://huggingface.co/spaces) that are ethically mindful, in order to highlight and encourage these kinds of projects – and we would love your input! | |
| If you have built a Space that you think should be featured, or if you would like to nominate someone else's, paste the URL in the form below 🤗 | |
| The current set of tags reflect our initial categorization from going through Hugging Face Spaces: 🤝 consentful, 🌎 sustainable, 👁️🗨️ socially conscious, 🧑🤝🧑 inclusive, ✍️ rigorous, and 🤔 inquisitive. | |
| Let us know other relevant categories and examples that you find! | |
| """) | |
| with gr.Accordion(label="Want to learn more? Visit us over on the Hugging Face Discord!", open=False): | |
| gr.Markdown(""" | |
| Follow these steps to join the discussion: | |
| 1. Go to [hf.co/join/discord](https://hf.co/join/discord) to join the Discord server. | |
| 2. Once you've registered, go to the `#role-assignment` channel. | |
| 3. Select the "Open Science" role. | |
| 4. Head over to `#ethics-and-society` to join the conversation 🥳 | |
| """, elem_id="margin-top") | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("💡 Click on the terms below to view their description and some examples.") | |
| with gr.Column(): | |
| [toggle_description(x["title"], x["content"]) for x in principles] | |
| with gr.Column(): | |
| URL = gr.Text(label="URL") | |
| tags = gr.Checkboxgroup( | |
| label="Tags - Pick as many as you like!", | |
| choices=[ | |
| "Consentful", | |
| "Sustainable", | |
| "Socially Conscious", | |
| "Inclusive", | |
| "Rigorous", | |
| "Inquisitive", | |
| ] | |
| ) | |
| suggestions = gr.Text(label="[Optional] Do you have suggestions for other tags?") | |
| comments = gr.TextArea(label="[Optional] Any extra comments?") | |
| submit = gr.Button(value="Submit") | |
| thank_you = gr.Markdown(visible=False) | |
| submit.click( | |
| fn=submit_entry, | |
| inputs=[URL, tags, suggestions, comments], | |
| outputs=[ | |
| thank_you, | |
| submit, | |
| URL, | |
| tags, | |
| suggestions, | |
| comments, | |
| ] | |
| ) | |
| hf_writer.setup( | |
| components=[URL, tags, suggestions, comments], | |
| flagging_dir="flagged" | |
| ) | |
| demo.launch() | |