Large Language Models (Latest)
Large Language Models (Latest)

Utilities

NIM includes a set of utility scripts to assist with NIM operation.

Utilities can be launched by adding the name of the desired utility to the docker run command. For example, you can execute the list-model-profiles utility with the following command:

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docker run --rm --runtime=nvidia --gpus=all $IMG_NAME list-model-profiles

You can get more information about each utility with the -h flag:

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docker run --rm --runtime=nvidia --gpus=all $IMG_NAME download-to-cache -h

list-model-profiles

Prints to the console the system information detected by NIM, and the list of all profiles for the chosen NIM. Profiles are categorized by whether or not they are compatible with the current system, based on the system information detected.

Example Output:

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SYSTEM INFO - Free GPUs: - [20b2:10de] (0) NVIDIA A100-SXM4-80GB (A100 80GB) [current utilization: 1%] - [20b2:10de] (1) NVIDIA A100-SXM4-80GB (A100 80GB) [current utilization: 1%] MODEL PROFILES - Compatible with system and runnable: - a93a1a6b72643f2b2ee5e80ef25904f4d3f942a87f8d32da9e617eeccfaae04c (tensorrt_llm-a100-fp16-tp2-latency) - 751382df4272eafc83f541f364d61b35aed9cce8c7b0c869269cea5a366cd08c (tensorrt_llm-a100-fp16-tp1-throughput) - 19031a45cf096b683c4d66fff2a072c0e164a24f19728a58771ebfc4c9ade44f (vllm-fp16-tp2) - 8835c31752fbc67ef658b20a9f78e056914fdef0660206d82f252d62fd96064d (vllm-fp16-tp1) - With LoRA support: - cce57ae50c3af15625c1668d5ac4ccbe82f40fa2e8379cc7b842cc6c976fd334 (tensorrt_llm-a100-fp16-tp1-throughput-lora) - c5ffce8f82de1ce607df62a4b983e29347908fb9274a0b7a24537d6ff8390eb9 (vllm-fp16-tp2-lora) - 8d3824f766182a754159e88ad5a0bd465b1b4cf69ecf80bd6d6833753e945740 (vllm-fp16-tp1-lora) - Incompatible with system: - dcd85d5e877e954f26c4a7248cd3b98c489fbde5f1cf68b4af11d665fa55778e (tensorrt_llm-h100-fp8-tp2-latency) - f59d52b0715ee1ecf01e6759dea23655b93ed26b12e57126d9ec43b397ea2b87 (tensorrt_llm-l40s-fp8-tp2-latency) - 30b562864b5b1e3b236f7b6d6a0998efbed491e4917323d04590f715aa9897dc (tensorrt_llm-h100-fp8-tp1-throughput) ...

download-to-cache

Downloads selected or default model profile(s) to NIM cache. Can be used to pre-cache profiles prior to deployment.

--profiles[PROFILES ...],-p[PROFILES ...]

Profile hashes to download. If none are provided, the optimal profile is downloaded. Multiple profiles can be specified separated by spaces.

--all

Set to download all profiles to cache

--lora

Set this to download default lora profile. This expects --profiles and --all arguments are not specified.

create-model-store

Extracts files from a cached model profile and creates a properly formatted directory. If the profile is not already cached, it will be downloaded to the model cache.

--profile<PROFILE>,-p<PROFILE>

Profile hash to create a model directory of. Will be downloaded if not present.

--model-store<MODEL_STORE>,-m<MODEL_STORE>

Directory path where model --profile will be extracted and copied to.

nim-llm-check-cache-env

Checks if the NIM cache directory is present and can be written to.

nim-llm-set-cache-env

Prints commands for setting cache environment variables to console.

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