# Deploy customized SpaCy NER transformer model to SageMaker

**URL:** <https://discuss.huggingface.co/t/deploy-customized-spacy-ner-transformer-model-to-sagemaker/20353>\
**Category:** Amazon SageMaker\
**Created:** [July 13, 2022, 8:02pm UTC](https://discuss.huggingface.co/t/deploy-customized-spacy-ner-transformer-model-to-sagemaker/20353 "2022-07-13T20:02:47Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![jinhybr](https://avatars.discourse-cdn.com/v4/letter/j/f9ae1b/32.png) [@jinhybr](https://discuss.huggingface.co/u/jinhybr)\
**Post date:** [July 13, 2022, 8:02pm UTC](https://discuss.huggingface.co/t/deploy-customized-spacy-ner-transformer-model-to-sagemaker/20353/1 "2022-07-13T20:02:47Z")

</div>

Hi ,  
I am deploying customized SpaCy NER transformer model to SageMaker. I got the inference errors…

```auto
odelError: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (400) from primary with message "{
  "code": 400,
  "type": "InternalServerException",
  "message": "Can\u0027t load config for \u0027/.sagemaker/mms/models/jinhybr __en_SEDNA_NER_MARTIME\u0027. Make sure that:\n\n- \u0027/.sagemaker/mms/models/jinhybr__ en_SEDNA_NER_MARTIME\u0027 is a correct model identifier listed on \u0027https://huggingface.co/models\u0027\n (make sure \u0027/.sagemaker/mms/models/jinhybr__en_SEDNA_NER_MARTIME\u0027 is not a path to a local directory with something else, in that case)\n\n- or \u0027/.sagemaker/mms/models/jinhybr__en_SEDNA_NER_MARTIME\u0027 is the correct path to a directory containing a config.json file\n\n"
}

```

Here is my deploy code:

```auto
from sagemaker.huggingface import HuggingFaceModel
import sagemaker 

role = sagemaker.get_execution_role()

# Hub Model configuration. https://huggingface.co/models
hub = {
  'HF_MODEL_ID':'jinhybr/en_SEDNA_NER_MARTIME', # model_id from hf.co/models
  'HF_TASK':'token-classification' # NLP task you want to use for predictions
}

# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
   env=hub,
   role=role, # iam role with permissions to create an Endpoint
   transformers_version="4.12.3", # transformers version used
   pytorch_version="1.9.1", # pytorch version used
   py_version="py38", # python version of the DLC
)
predictor = huggingface_model.deploy(
   initial_instance_count=1,
   instance_type="ml.m5.xlarge"
)
data = {
   "inputs": "Camera - You are awarded a SiPix Digital Camera! call 09061221066 fromm landline. Delivery within 28 days."
}

# request
predictor.predict(data)

```

I also try to deploy as zip from S3, same errors…here is s3 code.

```auto

huggingface_model = HuggingFaceModel(
   model_data="s3://hugg-ner-model/model.tar.gz", # path to your trained SageMaker model
   role=role, # IAM role with permissions to create an endpoint
   transformers_version="4.12.3", # Transformers version used
   pytorch_version="1.9.1", # PyTorch version used
   py_version='py38', # Python version used
    env={ 'HF_TASK':'token-classification' },
)
## I use tar zcvf model.tar.gz * from local repo and cp to s3

```

Really appreciated for your helps!

---

<div class="post-metadata">

**Author:** ![philschmid](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/philschmid/32/38022_2.png) [@philschmid](https://discuss.huggingface.co/u/philschmid)\
**Post date:** [July 14, 2022, 8:14am UTC](https://discuss.huggingface.co/t/deploy-customized-spacy-ner-transformer-model-to-sagemaker/20353/2 "2022-07-14T08:14:31Z")

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Hey @jinhybr,

The zero-code deployment through the `hub` configuration currently only works for `transformers` models and sadly not for spacy. To use spacy you would need to create a custom `inference.py` and `requirements.txt`. Similar to this example: [Creating document embeddings with Hugging Face's Transformers & Amazon SageMaker](https://www.philschmid.de/custom-inference-huggingface-sagemaker)

---

<div class="post-metadata">

**Author:** ![jinhybr](https://avatars.discourse-cdn.com/v4/letter/j/f9ae1b/32.png) [@jinhybr](https://discuss.huggingface.co/u/jinhybr)\
**Post date:** [August 3, 2022, 1:36pm UTC](https://discuss.huggingface.co/t/deploy-customized-spacy-ner-transformer-model-to-sagemaker/20353/3 "2022-08-03T13:36:29Z")

</div>

Thanks so much! I finally use the Docker Image /Lambda/API to deploy the customized Spacy model. It works