Spaces:
Runtime error
Runtime error
File size: 1,823 Bytes
6843958 b9ceb4f 6843958 b9ceb4f 6843958 |
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 |
import pandas as pd
import requests
from tqdm.auto import tqdm
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.repocard import metadata_load
# Based on Omar Sanseviero work
# Make model clickable link
def make_clickable_model(model_name):
# remove user from model name
model_name_show = ' '.join(model_name.split('/')[1:])
link = "https://huggingface.co/" + model_name
return f'<a target="_blank" href="{link}">{model_name_show}</a>'
# Make user clickable link
def make_clickable_user(user_id):
link = "https://huggingface.co/" + user_id
return f'<a target="_blank" href="{link}">{user_id}</a>'
def get_model_ids(rl_env):
api = HfApi()
models = api.list_models(filter=rl_env)
model_ids = [x.modelId for x in models]
return model_ids
def get_metadata(model_id):
try:
readme_path = hf_hub_download(model_id, filename="README.md")
return metadata_load(readme_path)
except requests.exceptions.HTTPError:
# 404 README.md not found
return None
def parse_metrics_accuracy(meta):
if "model-index" not in meta:
return None
result = meta["model-index"][0]["results"]
metrics = result[0]["metrics"]
accuracy = metrics[0]["value"]
return accuracy
# We keep the worst case episode
def parse_rewards(accuracy):
default_std = -1000
default_reward=-1000
if accuracy != None:
parsed = accuracy.split(' +/- ')
if len(parsed)>1:
mean_reward = float(parsed[0])
std_reward = float(parsed[1])
else:
mean_reward = float(default_std)
std_reward = float(default_reward)
else:
mean_reward = float(default_std)
std_reward = float(default_reward)
return mean_reward, std_reward
|