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Chapter 3. Downloading Large Language 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. You can upload any custom model to an S3 bucket.
| Large Language Models (LLMs) | Type | Size | Purpose | Model family | NVIDIA Accelerator Support | AMD Accelerator Support | Intel Accelerator Support |
|---|---|---|---|---|---|---|---|
|
| LAB fine-tuned granite starter model | 16.0 GB | Version 2 of the default Granite 3.1 base model for customizing and fine-tuning | Granite 3.1 | Generally Available | Generally Available | Not Available |
|
| LAB fine-tuned granite model | 16.0 GB | Version 2 of the default Granite 3.1 model for inference serving | Granite 3.1 | Generally Available | Generally Available | Not Available |
|
| LAB fine-tuned granite starter model | 16.0 GB | Version 2 of the default Granite 3.1 base model for customizing and fine-tuning | Granite 3.1 | Not Available | Not Available | Technology Preview |
|
| LAB fine-tuned granite model | 16.0 GB | Version 2 of the default Granite 3.1 model for inference serving | Granite 3.1 | Not Available | Not Available | Technology Preview |
|
| LAB fine-tuned granite code model | 15.0 GB | LAB fine-tuned granite code model for inference serving | Granite Code models | Technology Preview | Technology Preview | Technology Preview |
|
| Granite fine-tuned code model | 15.0 GB | Granite code model for inference serving | Granite Code models | Technology Preview | Technology Preview | Technology Preview |
|
| Default teacher model | 87.0 GB | Default teacher model for running Synthetic data generation (SDG) | Mixtral | Generally Available | Generally Available | Technology Preview |
|
| Optional teacher model | 74.0 GB | Optional teacher model for running Synthetic data generation (SDG) | Llama | Technology Preview | Not Available | Not Available |
|
| Evaluation judge model | 87.0 GB | Judge model for multi-phase training and evaluation | Prometheus 2 | Generally Available | Generally Available | Technology Preview |
Using the granite-8b-code-instruct or 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-starterorgranite-8b-starter-v1base LLM depending on your hardware vendor. -
The
mixtral-8x7b-instruct-v0-1teacher model for SDG. -
The
prometheus-8x7b-v2-0judge model for training and evaluation.
Additional tools required for customizing an LLM
The Low-rank adaptation (LoRA) adaptors enhance the efficiency of the Synthetic Data Generation (SDG) process.
-
The
skills-adapter-v3LoRA layered skills adapter for SDG. The
knowledge-adapter-v3LoRA layered knowledge adapter for SDG.Example command for downloading the adaptors
ilab model download --repository docker://registry.redhat.io/rhelai1/knowledge-adapter-v3 --release latest
$ ilab model download --repository docker://registry.redhat.io/rhelai1/knowledge-adapter-v3 --release latestCopy to Clipboard Copied! Toggle word wrap Toggle overflow
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.
3.1. Downloading the models from a Red Hat repository 링크 복사링크가 클립보드에 복사되었습니다!
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
To download the additional LLM models, run the following command:
ilab model download --repository docker://<repository_and_model> --release <release>
$ ilab model download --repository docker://<repository_and_model> --release <release>Copy to Clipboard Copied! Toggle word wrap Toggle overflow 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
1.5for the models that are supported on RHEL AI version 1.5. Set tolatestfor the latest version of the model.
Example command
ilab model download --repository docker://registry.redhat.io/rhelai1/granite-3.1-8b-starter-v1 --release latest
$ ilab model download --repository docker://registry.redhat.io/rhelai1/granite-3.1-8b-starter-v1 --release latestCopy to Clipboard Copied! Toggle word wrap Toggle overflow
Verification
You can view all the downloaded models, including the new models after training, on your system with the following command:
ilab model list
$ ilab model listCopy to Clipboard Copied! Toggle word wrap Toggle overflow Example output
Copy to Clipboard Copied! Toggle word wrap Toggle overflow You can also list the downloaded models in the
ls ~/.cache/instructlab/modelsfolder by running the following command:ls ~/.cache/instructlab/models
$ ls ~/.cache/instructlab/modelsCopy to Clipboard Copied! Toggle word wrap Toggle overflow Example output
granite-3.1-8b-starter-v1 granite-3.1-8b-lab-v1
granite-3.1-8b-starter-v1 granite-3.1-8b-lab-v1Copy to Clipboard Copied! Toggle word wrap Toggle overflow