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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) | |
| compatible_models = api.list_models(filter=filt) | |
| return [model.modelId for model in compatible_models] | |