phoenix-oss/llama-stack
1
0
Fork 0
forked from phoenix-oss/llama-stack-mirror
Code Pull requests Releases Packages 2 Activity Actions
llama-stack/docs/source/references/llama_cli_reference/download_models.md
Reid 4e76d312fa
fix: modify the model id title for model list (#1095) 
# What does this PR do?
[Provide a short summary of what this PR does and why. Link to relevant
issues if applicable.]

Re-check and based on the doc, the download model id, actually is model
descriptor(also without `meta-llama/`).


https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/index.html
```
$ llama download --source huggingface --model-id  Llama-Guard-3-1B:int4 --hf-token xxx  # model descriptor
Fetching 8 files:   0%|                                                                                                                   | 0/8 [00:00<?, ?it/s]
LICENSE.txt: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 7.71k/7.71k [00:00<00:00, 10.5MB/s]

$ llama download --source huggingface --model-id  Llama-Guard-3-1B-INT4 --hf-token xxxx  # hugging face repo without meta-llama/
usage: llama download [-h] [--source {meta,huggingface}] [--model-id MODEL_ID] [--hf-token HF_TOKEN] [--meta-url META_URL] [--max-parallel MAX_PARALLEL]
                      [--ignore-patterns IGNORE_PATTERNS] [--manifest-file MANIFEST_FILE]
llama download: error: Model Llama-Guard-3-1B-INT4 not found <<<<---


$ llama download --source meta --model-id Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8
usage: llama download [-h] [--source {meta,huggingface}] [--model-id MODEL_ID] [--hf-token HF_TOKEN] [--meta-url META_URL] [--max-parallel MAX_PARALLEL]
                      [--ignore-patterns IGNORE_PATTERNS] [--manifest-file MANIFEST_FILE]
llama download: error: Model Llama-3.2-3B-Instruct-SpinQuant_INT4_EO8 not found

$ llama download --source meta --model-id Llama3.2-3B-Instruct:int4-spinquant-eo8
Please provide the signed URL for model Llama3.2-3B-Instruct:int4-spinquant-eo8 you received via email after visiting https://www.llama.com/llama-downloads/ (e.g., https://llama3-1.llamameta.net/*?Policy...): ^CTraceback (most recent call last):

$ llama download --source meta --model-id meta-llama/Llama3.2-3B-Instruct:int4-spinquant-eo8
usage: llama download [-h] [--source {meta,huggingface}] [--model-id MODEL_ID] [--hf-token HF_TOKEN] [--meta-url META_URL]
                      [--max-parallel MAX_PARALLEL] [--ignore-patterns IGNORE_PATTERNS] [--manifest-file MANIFEST_FILE]
llama download: error: Model meta-llama/Llama3.2-3B-Instruct:int4-spinquant-eo8 not found
```

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)

Signed-off-by: reidliu <reid201711@gmail.com>
Co-authored-by: reidliu <reid201711@gmail.com>
2025-02-18 10:26:41 -08:00

8.1 KiB
Raw Blame History

Downloading Models

The llama CLI tool helps you setup and use the Llama Stack. It should be available on your path after installing the llama-stack package.

Installation

You have two ways to install Llama Stack:

  1. Install as a package: You can install the repository directly from PyPI by running the following command:

    pip install llama-stack

  2. Install from source: If you prefer to install from the source code, follow these steps:

     mkdir -p ~/local
 cd ~/local
 git clone git@github.com:meta-llama/llama-stack.git

 conda create -n myenv python=3.10
 conda activate myenv

 cd llama-stack
 $CONDA_PREFIX/bin/pip install -e .

Downloading models via CLI

You first need to have models downloaded locally.

To download any model you need the Model Descriptor. This can be obtained by running the command

llama model list

You should see a table like this:

+----------------------------------+------------------------------------------+----------------+
| Model Descriptor(ID)             | Hugging Face Repo                        | Context Length |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-8B                      | meta-llama/Llama-3.1-8B                  | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-70B                     | meta-llama/Llama-3.1-70B                 | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B:bf16-mp8           | meta-llama/Llama-3.1-405B                | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B                    | meta-llama/Llama-3.1-405B-FP8            | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B:bf16-mp16          | meta-llama/Llama-3.1-405B                | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-8B-Instruct             | meta-llama/Llama-3.1-8B-Instruct         | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-70B-Instruct            | meta-llama/Llama-3.1-70B-Instruct        | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct:bf16-mp8  | meta-llama/Llama-3.1-405B-Instruct       | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct           | meta-llama/Llama-3.1-405B-Instruct-FP8   | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct:bf16-mp16 | meta-llama/Llama-3.1-405B-Instruct       | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-1B                      | meta-llama/Llama-3.2-1B                  | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-3B                      | meta-llama/Llama-3.2-3B                  | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-11B-Vision              | meta-llama/Llama-3.2-11B-Vision          | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-90B-Vision              | meta-llama/Llama-3.2-90B-Vision          | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-1B-Instruct             | meta-llama/Llama-3.2-1B-Instruct         | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-3B-Instruct             | meta-llama/Llama-3.2-3B-Instruct         | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-11B-Vision-Instruct     | meta-llama/Llama-3.2-11B-Vision-Instruct | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-90B-Vision-Instruct     | meta-llama/Llama-3.2-90B-Vision-Instruct | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-11B-Vision         | meta-llama/Llama-Guard-3-11B-Vision      | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-1B:int4-mp1        | meta-llama/Llama-Guard-3-1B-INT4         | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-1B                 | meta-llama/Llama-Guard-3-1B              | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-8B                 | meta-llama/Llama-Guard-3-8B              | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-8B:int8-mp1        | meta-llama/Llama-Guard-3-8B-INT8         | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Prompt-Guard-86M                 | meta-llama/Prompt-Guard-86M              | 128K           |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-2-8B                 | meta-llama/Llama-Guard-2-8B              | 4K             |
+----------------------------------+------------------------------------------+----------------+

To download models, you can use the llama download command.

Downloading from Meta

Here is an example download command to get the 3B-Instruct/11B-Vision-Instruct model. You will need META_URL which can be obtained from here. Note: You need to quote the META_URL

Download the required checkpoints using the following commands:

# download the 8B model, this can be run on a single GPU
llama download --source meta --model-id Llama3.2-3B-Instruct --meta-url 'META_URL'

# you can also get the 70B model, this will require 8 GPUs however
llama download --source meta --model-id Llama3.2-11B-Vision-Instruct --meta-url 'META_URL'

# llama-agents have safety enabled by default. For this, you will need
# safety models -- Llama-Guard and Prompt-Guard
llama download --source meta --model-id Prompt-Guard-86M --meta-url 'META_URL'
llama download --source meta --model-id Llama-Guard-3-1B --meta-url 'META_URL'

Downloading from Hugging Face

Essentially, the same commands above work, just replace --source meta with --source huggingface.

llama download --source huggingface --model-id  Llama3.1-8B-Instruct --hf-token <HF_TOKEN>

llama download --source huggingface --model-id Llama3.1-70B-Instruct --hf-token <HF_TOKEN>

llama download --source huggingface --model-id Llama-Guard-3-1B --ignore-patterns *original*
llama download --source huggingface --model-id Prompt-Guard-86M --ignore-patterns *original*

Important: Set your environment variable HF_TOKEN or pass in --hf-token to the command to validate your access. You can find your token at https://huggingface.co/settings/tokens.

Tip: Default for llama download is to run with --ignore-patterns *.safetensors since we use the .pth files in the original folder. For Llama Guard and Prompt Guard, however, we need safetensors. Hence, please run with --ignore-patterns original so that safetensors are downloaded and .pth files are ignored.