File size: 2,668 Bytes
de1fc5c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
__all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissions']
import gradio as gr
import pandas as pd
from huggingface_hub import HfApi, repocard
def is_duplicated(space_id:str)->None:
card = repocard.RepoCard.load(space_id, repo_type="space")
return getattr(card.data, "duplicated_from", None) is not None
def make_clickable_model(model_name, link=None):
if link is None:
link = "https://huggingface.co/" + "spaces/" + model_name
return f'<a target="_blank" href="{link}">{model_name.split("/")[-1]}</a>'
def get_space_ids():
api = HfApi()
spaces = api.list_spaces(filter="jax-diffusers-event")
print(spaces)
space_ids = [x for x in spaces]
return space_ids
def make_clickable_user(user_id):
link = "https://huggingface.co/" + user_id
return f'<a target="_blank" href="{link}">{user_id}</a>'
def get_submissions():
submissions = get_space_ids()
leaderboard_models = []
for submission in submissions:
# user, model, likes
if not is_duplicated(submission.id):
user_id = submission.id.split("/")[0]
leaderboard_models.append(
(
make_clickable_user(user_id),
make_clickable_model(submission.id),
submission.likes,
)
)
df = pd.DataFrame(data=leaderboard_models, columns=["User", "Space", "Likes"])
df.sort_values(by=["Likes"], ascending=False, inplace=True)
df.insert(0, "Rank", list(range(1, len(df) + 1)))
return df
block = gr.Blocks()
with block:
gr.Markdown(
"""# JAX Diffusers Event Leaderboard
Welcome to the leaderboard for the JAX Diffusers Event 💗🏆
This is a community event where participants are creating applications based on Stable Diffusion using JAX and 🧨diffusers using v4 TPUs provided by Google Cloud.
To attend the event, simply follow the instructions in [this guide](https://github.com/huggingface/community-events/tree/main/jax-controlnet-sprint).
To submit your Space and add it to the leaderboard, simply add `jax-diffusers-event` under tags section in your Space's README.
At the end of the event, demos with most likes will be evaluated by the jury for special prizes! 🎁
"""
)
with gr.Row():
data = gr.components.Dataframe(
type="pandas", datatype=["number", "markdown", "markdown", "number"]
)
with gr.Row():
data_run = gr.Button("Refresh")
data_run.click(
get_submissions, outputs=data
)
block.load(get_submissions, outputs=data)
block.launch() |