Data Science now Supports Large Models
- Services: Data Science
- Release Date: June 21, 2024
Data Science Model Deployment and Model Catalog services now support large model deployments.
Large model artifacts can be stored in …
104 Release Notes | Page 1 of 3
Data Science Model Deployment and Model Catalog services now support large model deployments.
Large model artifacts can be stored in …
If you have models you want to use instead of those curated by Data Science, you can bring them into …
Deeplinking into a Notebook Session enables customers of OCI Data Science to open a notebook session at a file path …
Data Science ML Monitoring lets you:
AI quick actions makes it easy for you to browse a curated list of foundation models, and deploy, fine-tune, and …
Key Features
Some Key benefits of autoscaling for model deployment include:
Dynamic Resource Adjustment: Autoscaling automatically increases or decreases the number of …
The following conda environments are introduced:
Data Science notebooks now use JupyterLab version 3.6.6.
The following changes were made in ADS 2.10.1:
Releasing v1 of the Anomaly Detection Operator! The Anomaly Detection Operator is …
The following conda environments are introduced:
The following changes were made in ADS 2.10.0:
The following changes were made in ADS 2.9.1:
The following changes were made in ADS 2.9.0:
You can now specify File Storage service mount points or Object Storage service buckets in notebook sessions and jobs. This …
The following changes were made in ADS 2.8.11:
You can now use the notebook session lifecycle scripts to run a custom script at different notebook session lifecycle states …
You can now configure a private endpoint in your tenancy. Use a private endpoint to access one or more notebook …
The following changes were made in ADS 2.8.10:
LargeArtifactUploader class to understand OCI paths to upload model artifacts …The following changes were made in ADS 2.8.9:
scikit-learn dependency to >=1.0.pandas dependency to >1.2.1,<2.1 …The following changes were made in ADS 2.8.8:
PyTorchDistributed runtime option for Data Science jobs to add support for …The following changes were made in ADS 2.8.7:
opctl commands.The following changes were made in ADS 2.8.6:
ads opctl build-image job-local when the build of …The following changes were made in ADS 2.8.5:
key_content attribute in ads.set_auth() for the API KEY authentication. …The following changes were made in ADS 2.8.4:
ADSDataset from pandas dataframe.The following changes were made in ADS 2.8.3:
Added support for custom containers (Bring Your Own Container or BYOC), and …
The following changes were made in ADS 2.8.2:
Removed support for Python 3.7.
Improved the DataScienceMode.create() to support the timeout …
The following changes were made in ADS 2.8.1:
Fixed a bug for ads opctl run when --auth flag is passed …
Machine learning pipelines are a crucial component of the modern data science workflow. They help automate the process of building, …
The following changes were made in ADS 2.8.0:
Added support for the machine learning pipelines feature.
Fixed a bug in …
The following changes were made in ADS 2.7.3:
Added support for the model version set feature.
Added --job-info option to …
Model versioning enables you to keep records of the different models that you've trained, and your various attempts at improving …
We have simplified the process so that there is only one option to extend a notebook session to the maximum …
Data Science is now available in the US Midwest (Chicago) region.
For more information about Data Science and features in Cloud …
The following changes were made in ADS 2.7.0:
Fixed a bug in GenericModel.prepare. The .model-ignore file wasn't included in …
You can connect to Data Flow and run an Apache Spark application from a Data Science notebook session. These sessions …
The following changes were made in ADS 2.6.8 and ADS 2.6.7.
ads.dataset.helper to support Python …Accelerated Data Science added support for large models that are models with artifacts between 2 and 6 GB. An Object Storage …
See the …
The following changes were made in this version.
prepare_save_deploy() method to the GenericModel class. Now you can prepare model …You can now set up your notebook sessions with your often used custom environment variables and Git repos to be …
Data Science is now available in the Mexico Central (Queretaro) region.
For more information about Data Science and features in Cloud …
You can now use flexible compute shapes for model deployments.
For APIs, see CreateModelDeployment, and ModelDeploymentInstanceShapeConfigDetails.
For more …
The following changes were made in this version.
Added from_model_deployment() method to the GenericModel class. Now, you can load a …
The Environment Explorer tab list view has been updated with:
You can now build and use your own container for use when you create a job and job runs.
For …
The following changes were made in this version.
BDSSecretKeeper to store and save configuration parameters to connect to Big …