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try: |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer("BAAI/bge-m3") |
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sentences = [ |
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"That is a happy person", |
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"That is a happy dog", |
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"That is a very happy person", |
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"Today is a sunny day" |
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] |
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embeddings = model.encode(sentences) |
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similarities = model.similarity(embeddings, embeddings) |
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print(similarities.shape) |
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with open('BAAI_bge-m3_0.txt', 'w', encoding='utf-8') as f: |
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f.write('Everything was good in BAAI_bge-m3_0.txt') |
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except Exception as e: |
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import os |
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from slack_sdk import WebClient |
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client = WebClient(token=os.environ['SLACK_TOKEN']) |
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client.chat_postMessage( |
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channel='#exp-slack-alerts', |
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text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/BAAI_bge-m3_0.txt|BAAI_bge-m3_0.txt>', |
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) |
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with open('BAAI_bge-m3_0.txt', 'a', encoding='utf-8') as f: |
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import traceback |
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f.write('''```CODE: |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer("BAAI/bge-m3") |
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sentences = [ |
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"That is a happy person", |
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"That is a happy dog", |
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"That is a very happy person", |
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"Today is a sunny day" |
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] |
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embeddings = model.encode(sentences) |
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similarities = model.similarity(embeddings, embeddings) |
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print(similarities.shape) |
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# [4, 4] |
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``` |
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ERROR: |
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''') |
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traceback.print_exc(file=f) |
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finally: |
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from huggingface_hub import upload_file |
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upload_file( |
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path_or_fileobj='BAAI_bge-m3_0.txt', |
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repo_id='model-metadata/code_execution_files', |
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path_in_repo='BAAI_bge-m3_0.txt', |
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repo_type='dataset', |
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) |
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