AgentSkillsCN

hf-mem

通过命令行工具，估算从Hugging Face Hub加载Safetensors模型进行推理时所需的显存容量（适用于Transformers、Diffusers与Sentence Transformers等模型）。

SKILL.md
--- frontmatter
name: hf-mem
description: CLI to estimate the required VRAM to load Safetensors models for inference from the Hugging Face Hub (Transformers, Diffusers and Sentence Transformers)
license: mit

hf-mem

What it does

Estimates inference memory requirements for models on the Hugging Face Hub via Safetensors metadata with HTTP Range requests.

Requirements

  • •uv package manager (for uvx command)
  • •HF_TOKEN environment variable (only for gated/private models)

When to use

  • •User asks about model VRAM/memory needs
  • •User wants to check if a model fits in their GPU
  • •User provides a Hugging Face model URL or model ID

Usage

bash
uvx hf-mem --model-id <org/model-name>

Or add --experimental since hf-mem 0.4.3 to include KV cache estimations for LLMs and VLMs too.

Examples

  • •uvx hf-mem --model-id black-forest-labs/FLUX.1-dev
  • •uvx hf-mem --model-id mistralai/Mistral-7B-v0.1 --experimental

When it fails

  • •HTTP 401, if the model is gated/private, meaning you need to set HF_TOKEN with read access to it.
  • •HTTP 404, if the provided --model-id is not available on the Hugging Face Hub.
  • •RuntimeError, if none of model.safetensors, model.safetensors.index.json, or model_index.json is available.