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Cerebrium offers file management through a 50GB persistent volume that’s available to all apps in a project. This storage mounts at /persistent-storage and helps store model weights and files efficiently across deployments.
The /persistent-storage directory is not directly accessible during build time. You’ll need to use the Cerebrium CLI commands or the mounted volume at runtime to manage these files.

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Including Files in Deployments

The cerebrium.toml configuration file controls which files become part of the app: 
[cerebrium.deployment]
include = [
    "src/*.py",         # Python files in src.
    "config/*.json",    # JSON files in config.
    "requirements.txt"  # Specific files.
]

exclude = [
    "tests/*",          # Skip test files.
    "*.log"            # Skip log files.
]
Files included in deployments must be under 2GB each, with deployments working best for files under 1GB. Larger files should use persistent storage instead.

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Managing Persistent Storage

The CLI provides four commands for working with persistent storage.
At runtime, the volume is mounted at /persistent-storage. When using these commands, the Cerebrium CLI does not display the /persistent-storage/ portion of the path.
  1. Upload files with cerebrium cp: 
    # Upload to root directory
cerebrium cp src_file_name.txt

# Upload to specific location
cerebrium cp src_file_name.txt dest_file_name.txt

# Upload to directory
cerebrium cp dir_name sub_folder/
  2. List files with cerebrium ls: 
    # List root contents
cerebrium ls

# List specific folder
cerebrium ls sub_folder/
  3. Remove files with cerebrium rm: 
    # Remove a file
cerebrium rm file_name.txt

# Remove a directory
cerebrium rm folder_name
  4. Download files with cerebrium download: 
    # Download to current directory with same filename
cerebrium download file_name.txt

# Download with a different local filename
cerebrium download file_name.txt local_file_name.txt

# Download from a subdirectory
cerebrium download sub_folder/file_name.txt

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Using Stored Files

Here’s how to work with files in persistent storage: 
import os
import torch

# Load a model from persistent storage.
file_path = "/persistent-storage/segment-anything/sam_vit_h_4b8939.pth"
model = torch.jit.load(file_path)
During runtime on Cerebrium, your application should access files using the full /persistent-storage/ path. For example: 
# Read a file from persistent storage
with open("/persistent-storage/data/config.json", "r") as f:
    config = json.load(f)

# Write to persistent storage
with open("/persistent-storage/data/results.json", "w") as f:
    json.dump(results, f)

# Check if file exists in persistent storage
if os.path.exists("/persistent-storage/models/mymodel.pt"):
    model = torch.load("/persistent-storage/models/mymodel.pt")
Remember that while the CLI commands don’t display the /persistent-storage/ prefix in their output, your code must use the full path to access these files at runtime.

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Increasing Storage Capacity

The default 50GB persistent volume can be increased up to 1TB through self-service. The first 100GB is free, then $0.05 per GB per month.
  1. Via Dashboard: Navigate to your project and select Volumes. Click the three-dot menu on your volume and select Increase Size.
Volume resize option in the Cerebrium dashboard
  1. Via API: Use the resize volume endpoint:
curl -X POST "https://api.cerebrium.ai/v4/projects/{project_id}/volumes/{volume_id}/resize" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"newSizeGb": 200}'
For storage needs beyond 1TB, please contact support on Discord or via email.

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Storage Quota Errors

If you hit your storage quota, you’ll see errors like No space left on device when trying to download or write files. To resolve this:
  1. Remove unnecessary files from /persistent-storage using cerebrium rm
  2. Resize your volume to a larger capacity (up to 1TB self-service)
  3. Contact support for storage beyond 1TB