# Install custom python libraries in HuggingFace DLC **URL:** \ **Category:** Amazon SageMaker\ **Created:** [August 4, 2022, 12:12pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242 "2022-08-04T12:12:09Z")\ **Posts on this page:** 10\ **Page:** 1
**Author:** ![bluePenguin](https://avatars.discourse-cdn.com/v4/letter/b/da6949/32.png) [@bluePenguin](https://discuss.huggingface.co/u/bluePenguin)\ **Post date:** [August 4, 2022, 12:12pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/1 "2022-08-04T12:12:09Z")
Hi, I have the source code for a custom data cleaning library; the code is private to my company. I usually install it from local source using something ‘pip install ./cleanse’. I know the requirements.txt file can be used to specify package versions for public libraries like pandas and NumPy but how can we install custom packages in the HuggingFace DLC? ---
**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:** [August 8, 2022, 6:21am UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/2 "2022-08-08T06:21:15Z")
You can put `./cleanse` into you `source_dir` and then either add `os.system("pip install ./cleanse")` at the top of your training script or add the local path `./cleanse` into a `requirements.txt` in the `source_dir`. ---
**Author:** ![bluePenguin](https://avatars.discourse-cdn.com/v4/letter/b/da6949/32.png) [@bluePenguin](https://discuss.huggingface.co/u/bluePenguin)\ **Post date:** [August 8, 2022, 1:40pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/3 "2022-08-08T13:40:29Z")
Hi, I’m actually using this library to clean in inference. Is there a place I could leverage the inference.py file inside the code/ directory in the model.tar.gz file? Or otherwise can I somehow integrate the into the preprocess script (using SKLearnProcessor) ---
**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:** [August 8, 2022, 2:03pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/4 "2022-08-08T14:03:47Z")
Sorry, i am not sure what you mean with `Is there a place I could leverage the inference.py file inside the code/ directory in the model.tar.gz file? ` ---
**Author:** ![bluePenguin](https://avatars.discourse-cdn.com/v4/letter/b/da6949/32.png) [@bluePenguin](https://discuss.huggingface.co/u/bluePenguin)\ **Post date:** [August 8, 2022, 2:10pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/5 "2022-08-08T14:10:05Z")
I’m using an inference.py file right now as per instructions [at the bottom of this page](https://github.com/aws/sagemaker-huggingface-inference-toolkit#-user-defined-codemodules) to override defaults during model inference. I’m wondering how/if I can use the custom library within this file ---
**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:** [August 8, 2022, 2:17pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/6 "2022-08-08T14:17:46Z")
> [@philschmid](#): > > You can put `./cleanse` into you `source_dir` and then either add `os.system("pip install ./cleanse")` at the top of your training script or add the local path `./cleanse` into a `requirements.txt` in the `source_dir`. ^like that ---
**Author:** ![bluePenguin](https://avatars.discourse-cdn.com/v4/letter/b/da6949/32.png) [@bluePenguin](https://discuss.huggingface.co/u/bluePenguin)\ **Post date:** [August 8, 2022, 2:24pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/7 "2022-08-08T14:24:09Z")
What is source\_dir though? Like where is that argument specified ---
**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:** [August 8, 2022, 2:35pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/8 "2022-08-08T14:35:52Z")
How are you deploying your model currently? could you share the code snippet? `source_dir` refers to the `HuggingFaceModel` of the `sagemaker-sdk`. ---
**Author:** ![bluePenguin](https://avatars.discourse-cdn.com/v4/letter/b/da6949/32.png) [@bluePenguin](https://discuss.huggingface.co/u/bluePenguin)\ **Post date:** [August 8, 2022, 2:43pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/9 "2022-08-08T14:43:13Z")
```auto # create Hugging Face Model Class huggingface_model = HuggingFaceModel( model_data= model_uri, # path to your trained sagemaker model role=role, # iam role with permissions to create an Endpoint transformers_version="4.17", # transformers version used pytorch_version="1.10", # pytorch version used py_version="py38", env={ 'HF_TASK':'text-classification' }# python version of the DLC ) ``` ---
**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:** [August 8, 2022, 2:55pm UTC](https://discuss.huggingface.co/t/install-custom-python-libraries-in-huggingface-dlc/21242/10 "2022-08-08T14:55:27Z")
does the `model_uri` contain a `code/inference.py` ? If so you need to put the requirements.txt / `./cleanse` into the `code/` directory.