# "No space left on device" when using HuggingFace + SageMaker

**URL:** <https://discuss.huggingface.co/t/no-space-left-on-device-when-using-huggingface-sagemaker/5406>\
**Category:** Amazon SageMaker\
**Created:** [April 10, 2021, 12:07pm UTC](https://discuss.huggingface.co/t/no-space-left-on-device-when-using-huggingface-sagemaker/5406 "2021-04-10T12:07:55Z")\
**Posts on this page:** 1\
**Showing post:** 28

<div class="post-metadata">

**Author:** ![MaximusDecimusMeridi](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/maximusdecimusmeridi/32/3390_2.png) [@MaximusDecimusMeridi](https://discuss.huggingface.co/u/MaximusDecimusMeridi)\
**Post date:** [April 21, 2022, 2:21am UTC](https://discuss.huggingface.co/t/no-space-left-on-device-when-using-huggingface-sagemaker/5406/28 "2022-04-21T02:21:11Z")

</div>

Thanks for clarification. It looks to me under “Training DLC Overview” that the versions should be

```auto
estimator = HuggingFace(
                entry_point = 'train.py', # fine-tuning script used in training jon
                source_dir = 'embed_source', # directory where fine-tuning script is stored
                instance_type = instance_type, # instances type used for the training job
                instance_count = 1, # the number of instances used for training
                role = get_execution_role(), # Iam role used in training job to access AWS ressources, 
                transformers_version = '4.17.0', # the transformers version used in the training job
                max_run= 36000,
                pytorch_version = '1.10.2', # the pytorch_version version used in the training job
                py_version = 'py38', # the python version used in the training job
                hyperparameters = hyperparameters, # the hyperparameter used for running the training job
                metric_definitions = metric_definitions, # the metrics regex definitions to extract logs
                output_path=os.path.join(dataconnector.version_s3_prefix, "models"),
                code_location=os.path.join(dataconnector.version_s3_prefix, "models"),
                volume_size = 200,
                checkpoint_s3_uri='s3://kj-temp/checkpoints'

```

However, this fails with

`ClientError: TrainingHostAgent Initialization failed:API error (404): manifest for 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.10.2-transformers4.17.0-gpu-py38-cu110-ubuntu18.04 not found: manifest unknown: Requested image not found`

Based on [this post](https://discuss.huggingface.co/t/transformers-4-9-0-on-sagemaker/9145/9) I tried passing

`image_uri = '763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-cpu-py38-ubuntu20.04-v1.0',`

But now the training job fails with

`FileNotFoundError: [Errno 2] No such file or directory: 'train'`

What should I be passing to use the latest DLC in training?

---

_[View the full topic](https://discuss.huggingface.co/t/no-space-left-on-device-when-using-huggingface-sagemaker/5406)._