model-metadata/code_python_files
013k
1# /// script2# requires-python = ">=3.12"3# dependencies = [4# "numpy",5# "einops",6# "pandas",7# "matplotlib",8# "protobuf",9# "torch",10# "sentencepiece",11# "torchvision",12# "transformers",13# "timm",14# "diffusers",15# "sentence-transformers",16# "accelerate",17# "peft",18# "slack-sdk",19# ]20# ///21 22try:23 from sentence_transformers import CrossEncoder24 25 model = CrossEncoder("zeroentropy/zerank-2")26 27 query = "Which planet is known as the Red Planet?"28 passages = [29 "Venus is often called Earth's twin because of its similar size and proximity.",30 "Mars, known for its reddish appearance, is often referred to as the Red Planet.",31 "Jupiter, the largest planet in our solar system, has a prominent red spot.",32 "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."33 ]34 35 scores = model.predict([(query, passage) for passage in passages])36 print(scores)37 with open('zeroentropy_zerank-2_0.txt', 'w', encoding='utf-8') as f:38 f.write('Everything was good in zeroentropy_zerank-2_0.txt')39except Exception as e:40 import os41 from slack_sdk import WebClient42 client = WebClient(token=os.environ['SLACK_TOKEN'])43 client.chat_postMessage(44 channel='#hub-model-metadata-snippets-sprint',45 text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zeroentropy_zerank-2_0.txt|zeroentropy_zerank-2_0.txt>',46 )47 48 with open('zeroentropy_zerank-2_0.txt', 'a', encoding='utf-8') as f:49 import traceback50 f.write('''```CODE: 51from sentence_transformers import CrossEncoder52 53model = CrossEncoder("zeroentropy/zerank-2")54 55query = "Which planet is known as the Red Planet?"56passages = [57 "Venus is often called Earth's twin because of its similar size and proximity.",58 "Mars, known for its reddish appearance, is often referred to as the Red Planet.",59 "Jupiter, the largest planet in our solar system, has a prominent red spot.",60 "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."61]62 63scores = model.predict([(query, passage) for passage in passages])64print(scores)65```66 67ERROR: 68''')69 traceback.print_exc(file=f)70 71finally:72 from huggingface_hub import upload_file73 upload_file(74 path_or_fileobj='zeroentropy_zerank-2_0.txt',75 repo_id='model-metadata/code_execution_files',76 path_in_repo='zeroentropy_zerank-2_0.txt',77 repo_type='dataset',78 )79 