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Chapter 3. Downloading models

Red Hat Enterprise Linux AI allows you to customize or chat with various Large Language Models (LLMs) provided and built by Red Hat and IBM. You can download these models from the Red Hat RHEL AI registry.

Expand
Table 3.1. Red Hat Enterprise Linux AI LLMs
Large Language Models (LLMs)TypeSizePurposeSupport

granite-7b-starter

Base model

12.6 GB

Base model for customizing, training and fine-tuning

General availability

granite-7b-redhat-lab

LAB fine-tuned granite model

12.6 GB

Granite model for serving and inferencing

General availability

granite-8b-code-instruct

LAB fine-tuned granite code model

15.0 GB

LAB fine-tuned granite code model for serving and inferencing

Technology preview

granite-8b-code-base

Granite fine-tuned code model

15.0 GB

Granite code model for serving and inferencing

Technology preview

mixtral-8x7b-instruct-v0-1

Teacher/critic model

87.0 GB

Teacher and critic model for running Synthetic data generation (SDG)

General availability

prometheus-8x7b-v2-0

Judge model

87.0 GB

Judge model for multi-phase training and evaluation

General availability

Important

Using the `granite-8b-code-instruct` and `granite-8b-code-base` Large Language models (LLMS) is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.

Models required for customizing the Granite LLM

  • The granite-7b-starter base LLM.
  • The mixtral-8x7b-instruct-v0-1 teacher model for SDG.
  • The prometheus-8x7b-v2-0 judge model for training and evaluation.

Additional tools required for customizing an LLM

  • The skills-adapter-v3 LoRA layered skills adapter for SDG.
  • The knowledge-adapter-v3 LoRA layered knowledge adapter for SDG.
Important

The LoRA layered adapters do not show up in the output of the ilab model list command. You can see the skills-adapter-v3 and knowledge-adapter-v3 files in the ls ~/.cache/instructlab/models folder.

Note

The listed granite models for serving and inferencing are not currently supported for customizing.

You can download the additional optional models created by Red Hat and IBM.

Prerequisites

  • You installed RHEL AI with the bootable container image.
  • You initialized InstructLab.
  • You created a Red Hat registry account and logged in on your machine.
  • You have root user access on your machine.

Procedure

  1. To download the additional LLM models, run the following command: 

    $ ilab model download --repository docker://<repository_and_model> --release 1.1

    where:

    <repository_and_model>
    Specifies the repository location of the model as well as the model. You can access the models from the registry.redhat.io/rhelai1/ repository.
    <release>
    Specifies the version of the model. Set to 1.1 for the models that are supported on RHEL AI version 1.1.

    Example command

    $ ilab model download --repository docker://registry.redhat.io/rhelai1/granite-7b-starter --release latest

Verification

  1. You can view all the downloaded models, including the new models after training, on your system with the following command: 

    $ ilab model list

    Example output

    +-----------------------------------+---------------------+---------+
| Model Name                        | Last Modified       | Size    |
+-----------------------------------+---------------------+---------+
| models/prometheus-8x7b-v2-0       | 2024-08-09 13:28:50 |  87.0 GB|
| models/mixtral-8x7b-instruct-v0-1 | 2024-08-09 13:28:24 |  87.0 GB|
| models/granite-7b-redhat-lab      | 2024-08-09 14:28:40 |  12.6 GB|
| models/granite-7b-starter         | 2024-08-09 14:40:35 |  12.6 GB|
+-----------------------------------+---------------------+---------+

  2. You can also list the downloaded models in the ls ~/.cache/instructlab/models folder by running the following command: 

    $ ls ~/.cache/instructlab/models

    Example output

    granite-7b-starter
granite-7b-redhat-lab

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