SambaStudio release notes

Creating train jobs using the GUI.

Creating batch inference jobs using the GUI.

Creating endpoints using the GUI.

Tenant management using the GUI.

You can use your trained Hubert ASR models to create a new ASR pipeline with diarization (Diarization ASR Pipeline) or without diarization (ASR Pipeline).

A cleaner and more intuitive source selection process.

The ability to select a different local dataset before finalizing the adding a dataset from a local machine process.

A feedback statement when adding a dataset from a local machine stating to use the CLI process for datasets that are greater than 5GB or contain more than 1000 files.

The learning rate graph depicts the learning rate hyperparameter during the training run, allowing you monitor and optimize the balance between the quality of the final model with the required training time.

Added the ability to create multiple API keys for an endpoint.

Added the ability to revoke an endpoint API key to prevent further usage.

These features allow organizations to easily distribute and manage endpoints to different entities and users.

Previous versions of snapi dataset add commands and procedures are not compatible with release 23.11.1.

Adding a dataset using CLI commands results in faster uploads compared to using the GUI.

Using CLI commands to add datasets is recommended for datasets that are greater than 5GB or contain more than 1000 files.

The default tenant cannot be deleted.

All jobs, endpoints, datasets, and models created in the tenant will be deleted.

Associated users will no longer have access to the tenant.

RDUs allocated to the tenant will be added to the default tenant.

Tenant deletion is irreversible.

SambaStudio will now alert you if the required amount of storage space is not available for the following actions:

The Playground now includes a chat mode experience. Chat mode provides a word-by-word response to your prompt with follow-on prompts kept within the context of your conversation. This allows the Playground to understand your prompts without the need to restate preceding information.

Improved and updated the Add from presets drop-down menu and input field of the Playground editor for both chat and completion mode.

Renamed the tuning parameter Return logits to Top logprobs to align with the updated industry standard.

The new top menu bar provides access to the following information:

Provides users with flexible sharing options for datasets, models, and endpoints.

Organization datasets and models are now called Shared datasets and Shared models respectively.

Added new Tuning parameters, including Stop sequences, Return logits, Repetition penalty, and Top k.

Implemented tooltips for Tuning parameters and detailed information cards for each parameter.

The Playground now displays a token count for each submission. The display shows the total number of tokens for the current submission relative to the maximum number of tokens supported by the model (max sequence length).

Improved the visibility of the generated responses for each submission. Responses are displayed in the input/output field with highlighted blue text.

Improved the notification error if max sequence length is exceeded.

Updated and improved User presets, which include examples for each model and provide better understanding on how to best use models.

Updated design to include a more intuitive two-panel layout featuring a new model card design and filtering panel.

Improved the filtering and search functions to easily refine the display of corresponding models.

All available SambaNova provided models can easily be displayed by selecting the Available tab.

By default, new SambaNova models will not be automatically stored in an organization’s environment. This will allow organizations to save storage space.

Organization administrators (OrgAdmin) can download SambaNova models to the Model Hub that they wish to use for their organization.

Upcoming SambaNova models are visible to all users within the platform.

All users can view the model card of SambaNova Available models and contact their organization administrator (OrgAdmin) to download a model to the Model Hub. Downloaded models are available for use by the entire organization.

You no longer need to specify a Task during job or endpoint creation. Instead, you select a model to use directly during the workflow or use the new ML App field to filter the list of models to use.

Users can select multiple ML Apps while adding a dataset. This will help attach the same dataset with models under different ML Apps, for example Generative Tuning 1.5 and 13B models.

Improved dataset upload speed that will increase the upload speed of larger size datasets.

Significant number of refresh improvements to the Tenant management window, resulting in the improvement of tenant and organization level RDUs information displayed in the GUI.

Simplified tenant creation process by removing Display Name. Only the tenant name is required. Requirements for tenant name are displayed in the GUI during creation.

Selecting Extractive QA (Natural Questions) from the User preset drop-down, can cause the response code copied (Copy code) from the CLI option of View code, to fail when the response code is inputted into the terminal.

Selecting Sentiment Analysis (IMDB) from the User preset drop-down, can cause the response code copied (Copy code) from the Python SDK option of View code, to fail when the response code is inputted into the terminal.

A tenant is an allotment of users and resources within an organization. Organizations can leverage tenants for distinct purposes, such as development or production, and then share common resources across tenants. Each tenant has its own resources, users, and workloads. SambaStudio allows organizations to allocate resources across multiple tenants.

A user is part of an organization and can be assigned a predefined role: organization administrator, tenant administrator, or user. A user can be part of and assigned to multiple tenants. All users within the same tenant can view or manage projects and workloads present in the tenant. SambaStudio allows organizations to assign users across multiple tenants via the organization administrator or tenant administrator role.

The Model hub contains new search filters to narrow search results of model cards. The filters can be displayed by clicking the arrow > next to the Search field in the model hub.

The Playground now provides the ability to view and copy CURL, CLI, or Python SDK code blocks from the GUI.

New CLI commands for tenant management including creating, updating, and renaming tenants.

New CLI commands for user management including adding users, assigning roles, and deleting users.

Multiple email domains having the same username (account name) will create a conflict in SambaStudio. For example, a user with the email ab@c.com and a user with the email ab@d.com will create a conflict and be treated the same in the platform.

The number of characters for a username is limited to 36. If an admin tries to add a username that exceeds the character limit, the platform will not allow the operation and will produce an error.

Special characters such as period (.), dash (-), and underscore (_) are unsupported in usernames. For example, a user with the email jane.doe@domain.com would have a username jane.doe and is not supported.

The Model hub now provides model information details via model cards. The updated GUI includes a two-panel interface for viewing the SambaStudio model cards. The side-by-side panels display the model card list in the left panel and the content of the selected model card in the right panel.

The new Notifications panel displays platform specific messages in a scrollable list. Each notification includes a detailed heading, a tracking id number, and a creation timestamp. Notifications are further defined by type: Success, Info, Warnings, Errors, and Critical.

Added a column displaying the number of checkpoints associated with a project. Projects now display the number of associated jobs and endpoints.

Added a column displaying the status of the project. Provides visual feedback on project statuses. For example, Deleting will display when the project is in the process of being deleted from the platform.

Training jobs now include a Logs section that allows you to preview and download logs of your training session in the GUI. Logs can help you track progress, identify errors, and determine the cause of potential errors.

Editing endpoints in the GUI now allows users to choose a different model. This allows you to change the endpoint’s model negating the need to create a new endpoint for a different model.

The Playground now allows you to download the results of the last response provided.

Added a Return logits tuning parameter, which adjusts how many log probabilities to return along with predictions.

Dataflow-as-a-Service is now SambaStudio! The new name aligns with SambaNova’s commitment to bring industry-leading AI performance to applications and services.

SambaStudio allows users to add a model-checkpoint from a training job.

SambaStudio allows users to take a model from a different environment and add it as a new model to the current SambaStudio environment through NFS.

SambaStudio allows users to export any checkpoint they have published to the Model Hub. You can only export models associated with the My Models and Organizational Models groups. SambaNova Models cannot be exported from the platform.

Users can download the CLI and SDK packages directly from the Resources section of the SambaStudio platform.

This allows a deployed endpoint to be part of the semantic search pipeline.

Improved the user experience for restarting an endpoint.

Improved the user experience for adding datasets to the platform.