# InternalServerException when running a model loaded on S3
**URL:**
**Author:**  [@vicente-m47](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fvicente-m47)%5C
**Post date:** [August 5, 2021, 4:16pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Finternalserverexception-when-running-a-model-loaded-on-s3%2F9003%2F1 "2021-08-05T16:16:36Z")
Hi there,
I am trying to deploy a model loaded on S3, following the steps found mainly on this video: `[Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker](https://www.youtube.com/watch?v=pfBGgSGnYLs)`.
For that I have downloaded a model into a S3 bucket and use this image URI for DLC: image\_uri = “[763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:1.7.1-transformers4.6.1-cpu-py36-ubuntu18.04](http://763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:1.7.1-transformers4.6.1-cpu-py36-ubuntu18.04)”
When I run the `predictor.predict(data)` command, I get this error:
The model I use fot these tests is this one: dccuchile/bert-base-spanish-wwm-uncased, and I could not find the way for letting the model know which action should perform.
I am pretty new with HuggingFace technology, and probably I am missing the point for fixing that.
Please, could you let me know what should I do for informing the model about what to do?
Thank you!
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**Author:**  [@philschmid](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fphilschmid)%5C
**Post date:** [August 5, 2021, 4:32pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Finternalserverexception-when-running-a-model-loaded-on-s3%2F9003%2F2 "2021-08-05T16:32:47Z")
Hey @vicente-m47 ,
Could you please provide the whole code you executed?
If you want to deploy a model from [Models - Hugging Face](http://hf.co/models) you can use the “deploy” button on each of the model pages.
This will generate a code snippet for you
From reading the code you attached you are trying to send an input for `question-answering` to a model (dccuchile/bert-base-spanish-wwm-uncased), which is not fine-tuned for `question-answering`, also you are sending an English input to a Spanish model.
A good starting point for new Hugging Facer is our course at [Introduction - Hugging Face Course](http://hf.co/course).
You can find more information about deploying to sagemaker in the documentation here [Deploy models to Amazon SageMaker](https://huggingface.co/docs/sagemaker/inference)
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**Author:**  [@vicente-m47](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fvicente-m47)%5C
**Post date:** [August 6, 2021, 7:04am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Finternalserverexception-when-running-a-model-loaded-on-s3%2F9003%2F3 "2021-08-06T07:04:42Z")
Hi, @philschmid,
Sorry, you are right, my question was awfully written. Here is the code I used:
`!pip install sagemaker --upgrade`
```auto
from sagemaker.huggingface import HuggingFaceModel
import sagemaker
role = sagemaker.get_execution_role()
# This model was supposedly trained from the dccuchile Bert model for QA.
model = "s3://xxxxxxx/hg_model.tar.gz"
image_uri = "763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:1.7.1-transformers4.6.1-cpu-py36-ubuntu18.04"
huggingface_model = HuggingFaceModel(
model_data=model,
transformers_version='4.6.1',
pytorch_version='1.7.1',
py_version='py36',
image_uri=image_uri,
role=role,
)
```
```auto
predictor = huggingface_model.deploy(
initial_instance_count=1,
instance_type="ml.m5.xlarge"
)
```
```auto
data = {
"inputs": {
"question": "¿Cómo me llamo?",
"context": "Mi nombre es Juan y vivo en Francia"
}
}
predictor.predict(data)
```
Reading your comment, I understand that the problem should be on the trained model. I would review the course you recommend and check the training I did.
Thank you!
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**Author:**  [@philschmid](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fphilschmid)%5C
**Post date:** [August 6, 2021, 7:53am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Finternalserverexception-when-running-a-model-loaded-on-s3%2F9003%2F4 "2021-08-06T07:53:04Z")
You don’t need to provide an `image_uri` the HuggingFaceModel will select the right one based on `pytorch_version` and `transformers_version`.
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**Author:**  [@vicente-m47](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fvicente-m47)%5C
**Post date:** [August 6, 2021, 9:39am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Finternalserverexception-when-running-a-model-loaded-on-s3%2F9003%2F5 "2021-08-06T09:39:19Z")
Yes, you’re right. Thank you, @philschmid.