model-evaluator / utils.py
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lewtun HF staff
Add NER and filter for Transformers models
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import requests
from huggingface_hub import DatasetFilter, HfApi, ModelFilter
api = HfApi()
def get_auth_headers(token: str, prefix: str = "autonlp"):
return {"Authorization": f"{prefix} {token}"}
def http_post(
path: str,
token: str,
payload=None,
domain: str = None,
) -> requests.Response:
"""HTTP POST request to the AutoNLP API, raises UnreachableAPIError if the API cannot be reached"""
try:
response = requests.post(
url=domain + path, json=payload, headers=get_auth_headers(token=token), allow_redirects=True
)
except requests.exceptions.ConnectionError:
print("❌ Failed to reach AutoNLP API, check your internet connection")
response.raise_for_status()
return response
def get_metadata(dataset_name):
filt = DatasetFilter(dataset_name=dataset_name)
data = api.list_datasets(filter=filt, full=True)
return data[0].cardData["train-eval-index"]
def get_compatible_models(task, dataset_name):
filt = ModelFilter(task=task, trained_dataset=dataset_name, library="transformers")
compatible_models = api.list_models(filter=filt)
return [model.modelId for model in compatible_models]