mirror/gradio
2
0
Fork 0
mirror of https://github.com/gradio-app/gradio.git synced 2024-12-15 02:11:15 +08:00
Code Issues Packages Projects Releases Wiki Activity

website fixes

Browse Source
This commit is contained in:
Abubakar Abid 2021-12-16 14:13:59 -08:00
parent 1925b9d02c
commit 875840584a
2 changed files with 90 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
website/demos/run_demos.py
View File

@ -13,23 +13,20 @@ sys.path.insert(0, GRADIO_DEMO_DIR)
with open("demos.json") as demos_file:
demo_port_sets = json.load(demos_file)
print(demo_port_sets)
def launch_demo(demo_name, port):
demo_folder = os.path.join(GRADIO_DEMO_DIR, demo_name)
os.chdir(demo_folder)
with open('run.py', 'r') as file:
def launch_demo(demo_file):
subprocess.call(f"python {demo_file}", shell=True)
for demo_name, port in demo_port_sets:
demo_file = os.path.join(GRADIO_DEMO_DIR, demo_name, "run.py")
with open(demo_file, 'r') as file:
filedata = file.read()
filedata = filedata.replace(
f'if __name__ == "__main__":',
f'if __name__ == "__main__":\n iface.server_port={port}')
print(filedata)
with open('run.py', 'w') as file:
with open(demo_file, 'w') as file:
file.write(filedata)
subprocess.call(f"python run.py", shell=True)
for demo_name, port in demo_port_sets:
demo_thread = threading.Thread(target=launch_demo, args=(demo_name, port))
demo_thread = threading.Thread(target=launch_demo, args=(demo_file,))
demo_thread.start()
start_time = time.time()

98
website/homepage/src/other_templates/joining-huggingface_template.html
View File

@ -8,18 +8,21 @@
<title>Gradio x Huggingface</title>
<meta name="description" content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta name="description"
content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta name="author" content="Gradio">
<meta property="og:title" content="Gradio x Huggingface">
<meta property="og:type" content="website">
<meta property="og:url" content="https://gradio.app/joining-huggingface">
<meta property="og:description" content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta property="og:description"
content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta property="og:image" content="https://gradio.app/assets/img/acquisition_card.png">
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:creator" content="@teamGradio">
<meta name="twitter:title" content="Gradio x Huggingface">
<meta name="twitter:description" content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta name="twitter:image" content="https://gradio.app/assets/img/acquisition_card.png">
<meta name="twitter:description"
content="Gradio is joining Hugging Face! Read more about how we plan on working with Hugging Face to democratize access to the best machine learning applications.">
<meta name="twitter:image" content="https://gradio.app/assets/img/acquisition_card.png">
<link rel="icon" type="image/png" href="/assets/img/logo.png">
<link rel="stylesheet" href="/style.css">
@ -35,19 +38,22 @@
<img src="/assets/img/logo.svg" class="h-10">
</a>
<nav class="flex gap-12 sm:gap-16">
<div class="group relative cursor-pointer font-semibold flex items-center gap-1" onClick="document.querySelector('.guide-menu').classList.toggle('flex'); document.querySelector('.guide-menu').classList.toggle('hidden');">
<div class="group relative cursor-pointer font-semibold flex items-center gap-1"
onClick="document.querySelector('.guide-menu').classList.toggle('flex'); document.querySelector('.guide-menu').classList.toggle('hidden');">
Guides
<svg class="h-4 w-4" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20">
<path d="M9.293 12.95l.707.707L15.657 8l-1.414-1.414L10 10.828 5.757 6.586 4.343 8z" />
</svg>
<div class="guide-menu hidden group-hover:flex group-active:flex flex-col absolute top-6 left-0 bg-white shadow w-52">
<div
class="guide-menu hidden group-hover:flex group-active:flex flex-col absolute top-6 left-0 bg-white shadow w-52">
{% for guide_name, pretty_guide_name in guide_names %}
<a class="link px-4 py-2 inline-block hover:bg-gray-100" href="/{{ guide_name }}">{{ pretty_guide_name }}</a>
{% endfor %}
</div>
</div>
<a class="link" href="/docs">Docs</a>
<div class="group relative cursor-pointer font-semibold flex items-center gap-1" onClick="document.querySelector('.help-menu').classList.toggle('flex'); document.querySelector('.help-menu').classList.toggle('hidden');">
<div class="group relative cursor-pointer font-semibold flex items-center gap-1"
onClick="document.querySelector('.help-menu').classList.toggle('flex'); document.querySelector('.help-menu').classList.toggle('hidden');">
Help
<svg class="h-4 w-4" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20">
<path d="M9.293 12.95l.707.707L15.657 8l-1.414-1.414L10 10.828 5.757 6.586 4.343 8z" />
@ -66,16 +72,61 @@
<div class="prose prose-lg max-w-none">
<h2>We are joining Hugging Face!</h2>
<p>Abubakar Abid, CEO of Gradio</p>
<p class="italic">Gradio is joining Hugging Face! By acquiring Gradio, a machine learning startup, Hugging Face will be able to offer users, developers, and data scientists the tools needed to get to high level results and create better models and tools...</p>
<p>Hmm, paragraphs about acquisitions like the one above are so common that an algorithm could write them. In fact, one did!! This first paragraph was written with the <a href="https://huggingface.co/spaces/abidlabs/The-Acquisition-Post-Generator">Acquisition Post Generator</a>, a machine learning demo on Hugging Face Spaces. You can run it yourself in your browser: provide the names of any two companies and you'll get a reasonable-sounding start to an article announcing their acquisition!</p>
<p>The Acquisition Post Generator was built using our open-source Gradio library -- it is just one of our recent collaborations with Hugging Face. And I'm excited to announce that these collaborations are culminating in... 🥁 <strong>Hugging Face's acquisition of Gradio</strong> (so yes, that first paragraph might have been written by an algorithm but it's true!)</p>
<p class="italic">Gradio is joining Hugging Face! By acquiring Gradio, a machine learning startup, Hugging Face
will be able to offer users, developers, and data scientists the tools needed to get to high level results and
create better models and tools...</p>
<p>Hmm, paragraphs about acquisitions like the one above are so common that an algorithm could write them. In
fact, one did!! This first paragraph was written with the <a
href="https://huggingface.co/spaces/abidlabs/The-Acquisition-Post-Generator">Acquisition Post Generator</a>, a
machine learning demo on Hugging Face Spaces. You can run it yourself in your browser: provide the names of any
two companies and you'll get a reasonable-sounding start to an article announcing their acquisition!</p>
<p>The Acquisition Post Generator was built using our open-source Gradio library -- it is just one of our recent
collaborations with Hugging Face. And I'm excited to announce that these collaborations are culminating in... 🥁
<strong>Hugging Face's acquisition of Gradio</strong> (so yes, that first paragraph might have been written by
an algorithm but it's true!)</p>
<img class="max-w-full mx-auto my-6" style="width: 54rem" src="/assets/img/acquisition_screenshot.png">
<p>As one of the founders of Gradio, I couldn't be more excited about the next step in our journey. I still remember clearly how we started in 2019: as a PhD student at Stanford, I struggled to share a medical computer vision model with one of my collaborators, who was a doctor. I needed him to test my machine learning model, but he didn't know Python and couldn't easily run the model on his own images. I envisioned a library that could make it super simple for machine learning engineers to build and share demos of computer vision models, which in turn would lead to better feedback and more reliable models 🔁</p>
<p>I recruited my talented housemates Ali Abdalla, Ali Abid, and Dawood Khan to release the first version of Gradio in 2019. We steadily expanded to cover more areas of machine learning including text, speech, and video. We found that it wasn't just researchers who needed to share machine learning models: interdisciplinary teams in industry, from startups to public companies, were building models and needed to debug them internally or showcase them externally. Gradio could help with both. Since we first released the library, more than 300,000 demos have been built with Gradio. We couldn't have done this without our community of contributors, our supportive investors, and the amazing Ahsen Khaliq who joined our company this year. </p>
<p>Demos and GUIs built with Gradio give the power of machine learning to more and more people because they allow non-technical users to access, use, and give feedback on models. And our acquisition by Hugging Face is the next step in this ongoing journey of accessibility. Hugging Face has already radically democratized machine learning so that any software engineer can use state-of-the-art models with a few lines of code. By working together with Hugging Face, we're taking this even further so that machine learning is accessible to literally anyone with an internet connection and a browser. With Hugging Face, we are going to keep growing Gradio and make it the best way to share your machine learning model with anyone, anywhere 🚀</p>
<p>In addition to the shared mission of Gradio and Hugging Face, what delights me is the team that we are joining. Hugging Face's remarkable culture of openness and innovation is well-known. Over the past few months, I've gotten to know the founders as well: they are wonderful people who genuinely care about every single person at Hugging Face and are willing to go to bat for them. On behalf of the entire Gradio team, we couldn't be more thrilled to be working with them to build the future of machine learning 🤗</p>
<p>As one of the founders of Gradio, I couldn't be more excited about the next step in our journey. I still
remember clearly how we started in 2019: as a PhD student at Stanford, I struggled to share a medical computer
vision model with one of my collaborators, who was a doctor. I needed him to test my machine learning model, but
he didn't know Python and couldn't easily run the model on his own images. I envisioned a library that could
make it super simple for machine learning engineers to build and share demos of computer vision models, which in
turn would lead to better feedback and more reliable models 🔁</p>
<p>I recruited my talented housemates Ali Abdalla, Ali Abid, and Dawood Khan to release the first version of
Gradio in 2019. We steadily expanded to cover more areas of machine learning including text, speech, and video.
We found that it wasn't just researchers who needed to share machine learning models: interdisciplinary teams in
industry, from startups to public companies, were building models and needed to debug them internally or
showcase them externally. Gradio could help with both. Since we first released the library, more than 300,000
demos have been built with Gradio. We couldn't have done this without our community of contributors, our
supportive investors, and the amazing Ahsen Khaliq who joined our company this year. </p>
<p>Demos and GUIs built with Gradio give the power of machine learning to more and more people because they allow
non-technical users to access, use, and give feedback on models. And our acquisition by Hugging Face is the next
step in this ongoing journey of accessibility. Hugging Face has already radically democratized machine learning
so that any software engineer can use state-of-the-art models with a few lines of code. By working together with
Hugging Face, we're taking this even further so that machine learning is accessible to literally anyone with an
internet connection and a browser. With Hugging Face, we are going to keep growing Gradio and make it the best
way to share your machine learning model with anyone, anywhere 🚀</p>
<p>In addition to the shared mission of Gradio and Hugging Face, what delights me is the team that we are joining.
Hugging Face's remarkable culture of openness and innovation is well-known. Over the past few months, I've
gotten to know the founders as well: they are wonderful people who genuinely care about every single person at
Hugging Face and are willing to go to bat for them. On behalf of the entire Gradio team, we couldn't be more
thrilled to be working with them to build the future of machine learning 🤗</p>
<p>Also: <a class="link" href="https://apply.workable.com/huggingface/">we are hiring!!</a> ❤️</p>
</div>
</div>
<div class="flex justify-center ">
<a class="border shadow border-gray-300 bg-gradient-to-b from-gray-50 to-gray-100 hover:to-gray-200 transition rounded inline-flex gap-2 items-center justify-center px-3 py-2 rounded-r-none"
href="https://github.com/gradio-app/gradio-UI" target="_blank"
aria-label="Star gradio-app/gradio-UI on GitHub">
<svg version="1.1" class="h-6" viewBox="0 0 14 16" class="inline" aria-hidden="true">
<path fill-rule="evenodd"
d="M14 6l-4.9-.64L7 1 4.9 5.36 0 6l3.6 3.26L2.67 14 7 11.67 11.33 14l-.93-4.74L14 6z"></path>
</svg>
<span class="text-md">Star</span>
</a>
<a class="font-semibold border shadow bg-white border-gray-300 hover:border-gray-400 transition hover:text-blue-600 rounded px-3 py-2 rounded-l-none border-l-0"
href="https://github.com/gradio-app/gradio/stargazers" target="_blank" aria-label="3902 stargazers on GitHub">
<span id="star-count" class="transition preloaded-star-count"></span>
</a>
</div>
</div>
<footer class="container mx-auto p-4 flex justify-between items-center">
<img src="/assets/img/logo.svg" class="h-10">
@ -88,6 +139,21 @@
</a>
</div>
</footer>
<script>
let xhr = new XMLHttpRequest;
xhr.open('GET', 'https://api.github.com/repos/gradio-app/gradio', true)
xhr.onload = function()
{
if (this.status === 200)
{
var stars = JSON.parse(this.responseText)["stargazers_count"];
stars = stars.toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",");
document.getElementById('star-count').innerHTML = stars;
document.getElementById('star-count').classList.remove("preloaded-star-count");
}
}
xhr.send();
</script>
</body>
</html>
</html>