hf endpoints deploy and update support container engine flags
Introduced 2026-08-07 · score 0.98
HOW TO USE IT
When deploying or tuning an Inference Endpoint with a managed engine image, set the command or arguments with the container flags; they do not require `--custom-image`. For an existing endpoint, pass the full replacement value, or an empty string to reset it; omit a flag to leave it unchanged.
hf endpoints deploy <endpoint-name> --repo gpt2 --framework pytorch --accelerator cpu --instance-size x2 --instance-type intel-icl --region us-east-1 --vendor aws --container-args "--max-model-len 8192"hf endpoints update <endpoint-name> --container-args "--enable-auto-tool-choice --tool-call-parser lfm2"hf endpoints update <endpoint-name> --container-args ""WHY THIS HELPS
When deploying or tuning an Inference Endpoint that uses a managed engine image, set or change its engine command or arguments.
BEFORE THIS CHANGE
The v1.26.0 guide showed CLI deployment with `--container-command` and `--container-args` alongside `--custom-image`; the release note says updating these values was previously available through the UI or raw API.
REQUIREMENTS AND LIMITATIONS
- Version: v1.27.0
- NAME / endpoint name (required): Name of the Inference Endpoint.
- --repo (required): Model repository for the endpoint.
- --framework (required): Machine learning framework used for the model.
- --accelerator (required): Hardware accelerator for inference.
- --instance-size (required): Instance size for hosting the model.
- --instance-type (required): Cloud instance type for deployment.
- --region (required): Cloud region for deployment.
- --vendor (required): Cloud provider for deployment.
- --container-command: Overrides the container entrypoint; pass a quoted string split into tokens. On update, replaces the current value; empty string clears it.
- --container-args: Sets arguments for the container entrypoint; pass a quoted string split into tokens. On update, replaces current arguments rather than adding to them; empty string clears them.
- container_command: Optional `list[str]` overriding the entrypoint; maps to `model.command` and works with managed engine and custom images.
- container_args: Optional `list[str]` of arguments for the entrypoint; maps to `model.args` and works with managed engine and custom images.
- Prerequisite: For deploy, the docs require valid `--vendor`, `--region`, `--accelerator`, `--instance-type`, and `--instance-size` combinations; `hf endpoints hardware` lists them.
- Prerequisite: The API update methods allow all arguments to be omitted, but require at least one update argument.
- `--health-route` and `--port` still require `--custom-image`.
- Values replace rather than append; an empty string resets to the image default, and omitting the flag leaves the value unchanged.
FIRST-PARTY EVIDENCE
- https://github.com/huggingface/huggingface_hub/releases/tag/v1.27.0
- https://huggingface.co/docs/huggingface_hub/en/package_reference/cli
- https://huggingface.co/docs/huggingface_hub/en/guides/cli
- https://huggingface.co/docs/huggingface_hub/main/package_reference/inference_endpoints
- https://huggingface.co/docs/huggingface_hub/v1.26.0/en/guides/inference_endpoints
Check the installed version and the source before using it. Entry JSON