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llama 3.1 ÊÇÒ»¿îÓÉ google ¿ª·¢µÄ ai ÓïÑÔÄ£×Ó£¬¿Éͨ¹ý gcp »á¼û¡£ËüµÄÖ÷ÒªÓÃÀý°üÀ¨Îı¾ÌìÉú¡¢·­Òë¡¢ÕªÒªºÍÎÊ´ð¡£Í¨¹ý python ´úÂ룬Äú¿ÉÒÔÖ±½ÓŲÓÃÆä api ¾ÙÐÐÕ¹Íû£¬ÀýÈçÌìÉúÎı¾¡£Ê¹Óà gcp ЧÀÍ£¬Äú¿ÉÒÔÀ©Õ¹ llama 3.1 µÄ¹¦Ð§£¬´¦Àí´ó¹æÄ£Îı¾Êý¾Ý¼¯²¢ÓÅ»¯ÐÔÄÜ¡£

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Llama 3.1 ÊÇÒ»¿îÏȽøµÄ AI ÓïÑÔÄ£×Ó£¬ÓÉ Google ¿ª·¢¡£ËüÓµÓÐÇ¿Ê¢µÄÎı¾ÌìÉú¡¢·­ÒëºÍÕªÒªµÈ×ÔÈ»ÓïÑÔ´¦ÀíÄÜÁ¦¡£

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Llama 3.1 ¿Éͨ¹ý Google Cloud Platform£¨GCP£©»á¼û¡£ÒªÊ¹ÓÃËü£¬Çëƾ֤ÒÔÏ°취²Ù×÷£º

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ͨ¹ý Google Cloud SDK »á¼û API¡£

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ÒÔÏ Python ´úÂëչʾÁËÔõÑùʹÓà Llama 3.1 ÌìÉúÎı¾£º

from google.cloud import aiplatform

# ÉèÖà API ¿Í»§¶Ë
client_options = {
    "api_endpoint": "us-central1-aiplatform.googleapis.com",
}
client = aiplatform.gapic.PredictionServiceClient(client_options=client_options)

# ÉèÖÃÄ£×ÓÃû³ÆºÍÊäÈëÎı¾
model_name = "projects/your-project/locations/your-location/models/llama-3-1"
text = "Generate a story about a lost dog."

# ÌᳫչÍûÇëÇó
response = client.predict(
    endpoint=model_name,
    instances=[{"content": text}],
    parameters={"num_results": 1},
)

# ´òÓ¡Õ¹ÍûЧ¹û
print(response.predictions[0])

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ʹÓà Google Cloud Storage ºÍ BigQuery µÈ GCP ЧÀÍÓë Llama 3.1 ¼¯³É£¬ÒÔ´¦Àí´ó¹æÄ£Îı¾Êý¾Ý¼¯¡£

ÒÔÉϾÍÊÇ×îÇ¿Ä£×Ó Llama 3.1 ÔõôÓõÄÏêϸÄÚÈÝ£¬¸ü¶àÇë¹Ø×¢±¾ÍøÄÚÆäËüÏà¹ØÎÄÕ£¡

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