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---
license: bigscience-bloom-rail-1.0
---
---
license: creativeml-openrail-m
---import json
import sagemaker
import boto3
from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri
try:
role = sagemaker.get_execution_role()
except ValueError:
iam = boto3.client('iam')
role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']
# Hub Model configuration. https://huggingface.co/models
hub = {
'HF_MODEL_ID':'intfloat/multilingual-e5-small'
}
# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
image_uri=get_huggingface_llm_image_uri("huggingface-tei",version="1.2.3"),
env=hub,
role=role,
)
# deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
initial_instance_count=1,
instance_type="ml.g5.2xlarge",
)
# send request
predictor.predict({
"inputs": "My name is Clara and I am",
}) |