Official agent skill

Hf Mem

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Hf Mem

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install huggingface/skills hf-mem --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hf-mem .claude/skills/hf-mem && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .claude/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/huggingface/skills/tree/main/skills/hf-mem

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install huggingface/skills hf-mem --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/hf-mem .agents/skills/hf-mem && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .agents/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install huggingface/skills hf-mem --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/hf-mem .cursor/skills/hf-mem && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .cursor/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/huggingface/skills.git --path skills/hf-mem

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install huggingface/skills hf-mem --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/hf-mem .gemini/skills/hf-mem && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .gemini/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install huggingface/skills hf-mem

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/hf-mem .github/skills/hf-mem && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .github/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add huggingface/skills --skill hf-mem -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install huggingface/skills hf-mem --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/hf-mem .opencode/skills/hf-mem && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "hf-mem" agent skill from https://github.com/huggingface/skills/tree/main/skills/hf-mem into .opencode/skills/hf-mem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hf-mem", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: hf-mem
GitHub stars: 11k
Used in: 4 other repos
Token cost: ~832 tokens
SKILL.md length: 318 words
Files: 1
Skills in repo: 25
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Tasks that involve Model hubs and datasets
SKILL.md covers When to use?, What are the requirements?, How to run? and Examples
Calls uvx; needs HF_TOKEN

What it does

Hf Mem is an agent skill from huggingface/skills, published by the product's own GitHub organization. Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Its SKILL.md is about 830 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Model hubs and datasets. It works with Hugging Face and llama.cpp. The repository describes itself as: Give your agents the power of the Hugging Face ecosystem. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Model hubs and datasets

Example prompts

“/hf-mem”

What it can do on your machine

Read from SKILL.md and the folder at commit c3ff942. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- uvx
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uvx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- HF_TOKEN
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hf Mem loads about 832 tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 318 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~34
When it runs · the whole SKILL.md, loaded when a task matches: ~832

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from huggingface/skills at commit c3ff942, republished under its Apache-2.0 licence (© huggingface). 318 words, ~832 tokens.

Download SKILL.mdSave it as .claude/skills/hf-mem/SKILL.md (or your agent's skills folder).

name: hf-mem
description: Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

hf_mem estimates the required memory for inference, including model weights and an optional KV cache, for Safetensors and GGUF for models on the Hugging Face Hub using HTTP Range requests i.e., without downloading or loading any weights locally.

When to use?

User asks how much VRAM or memory a model needs to run
User wants to know if a model fits on their GPU or a given instance
User references a Hugging Face model ID or URL and asks about inference requirements

What are the requirements?

uv installed (for uvx)
HF_TOKEN env var or --hf-token flag (for gated or private models only)

How to run?

Run with --model-id pointing to the Hugging Face Hub repository which will check that it either contains Safetensors (via model.safetensors, model.safetensors.index.json if sharded, or model_index.json for Diffusers) or GGUF model weights within.

bash

uvx hf-mem --model-id <model-id> --json-output

If the repository contains GGUF model weights in multiple precisions / quantizations, the estimations will be on a per-file basis, whereas for inference you won't load all of those but rather only a single precision. This being said, for GGUF you might as well need to provide --gguf-file to target the specific file (or path if sharded) you want to run.

bash

uvx hf-mem --model-id <model-id> --gguf-file <file-or-path> --json-output

Additionally, hf-mem comes with an --experimental flag that will also calculate the KV cache memory requirements too, useful for large-language models, meaning it applies to LLMs (...ForCausalLM), VLMs (...ForConditionalGeneration), and GGUF models.

As per the context window, it will be read from the default or overridden with --max-model-len a la vLLM. And, same goes for the KV cache precision, which will default to the model precision unless manually set via --kv-cache-dtype a la vLLM too.

For Safetensors use as:

bash

uvx hf-mem --model-id <model-id> --experimental [--max-model-len N] [--batch-size N] [--kv-cache-dtype auto|bfloat16|fp8|fp8_ds_mla|fp8_e4m3|fp8_e5m2|fp8_inc] --json-output

And, for GGUF use as:

bash

uvx hf-mem --model-id <model-id> --gguf-file <file-or-path> --experimental [--max-model-len N] [--batch-size N] [--kv-cache-dtype auto|F32|F16|Q4_0|Q4_1|Q5_0|Q5_1|Q8_0|Q8_1|Q2_K|Q3_K|Q4_K|Q5_K|Q6_K|Q8_K|IQ2_XXS|IQ2_XS|IQ3_XXS|IQ1_S|IQ4_NL|IQ3_S|IQ2_S|IQ4_XS|I8|I16|I32|I64|F64|IQ1_M|BF16|TQ1_0|TQ2_0|MXFP4] --json-output

Examples

For Transformers with Safetensors weights:

bash

uvx hf-mem --model-id MiniMaxAI/MiniMax-M2 --json-output

For Diffusers with Safetensors weights:

bash

uvx hf-mem --model-id Qwen/Qwen-Image --json-output

For Sentence Transformers with Safetensors weights:

bash

uvx hf-mem --model-id google/embeddinggemma-300m --json-output

With --experimental to include the KV cache estimation for LLMs and VLMs:

bash

uvx hf-mem --model-id mistralai/Mistral-7B-v0.1 --experimental --json-output

And, for LLMs or VLMs with GGUF weights:

bash

uvx hf-mem --model-id unsloth/Qwen3.5-397B-A17B-GGUF --gguf-file Q4_K_M --experimental --json-output

Files

Just SKILL.md in skills/hf-mem of huggingface/skills.

Open the folder on GitHubat commit c3ff942

Used in 4 other repositories

We found 9 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in huggingface/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Hf Mem next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hf Mem compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Hf Mem this skillhuggingface/skills	11k	4 repos	~832	Automated safety check: Pass	Apache-2.0	today
Qwen Mtp GgufR6410418/Jackrong-llm-finetuning-guide	1.7k	—	~1.7k	Automated safety check: Pass	MIT	3 mo ago
Add Modelguoqingbao/xinfer	334	—	~4.2k	Automated safety check: Notes	MIT	1 mo ago
Huggingface LLM Trainerwaybarrios/opencode-power-pack	533	—	~3k	Automated safety check: Pass	Apache-2.0	3 days ago
Resolvealexziskind1/model-shelf	130	—	~792	Automated safety check: Pass	MIT	1 mo ago
Xybrid Initxybrid-ai/xybrid	467	—	~3k	Automated safety check: Pass	Apache-2.0	today

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Works with

Questions about Hf Mem

What does Hf Mem do?

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub. Hf Mem is an agent skill from huggingface/skills, published by the product's own GitHub organization.

When should I use Hf Mem?

Hf Mem fits situations like: tasks that involve Model hubs and datasets.

How do I install Hf Mem in Claude Code?

Run `npx skills add huggingface/skills --skill hf-mem -a claude-code`. Or copy the skill folder (skills/hf-mem in huggingface/skills) into .claude/skills/hf-mem in your project. Claude Code loads it when a task matches its description.

How do I install Hf Mem in Codex?

Run `npx skills add huggingface/skills --skill hf-mem -a codex`. Or copy the skill folder (skills/hf-mem in huggingface/skills) into .agents/skills/hf-mem in your project. Codex loads it when a task matches its description.

Can I use Hf Mem in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add huggingface/skills --skill hf-mem -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hf-mem, .gemini/skills/hf-mem, .github/skills/hf-mem and .opencode/skills/hf-mem in your project.

What does Hf Mem need to run?

Going by SKILL.md and its folder, Hf Mem needs the command-line tools its instructions call (uvx) and credentials named HF_TOKEN.

Does Hf Mem access the network?

SKILL.md contains no URLs. Its commands use uvx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Hf Mem safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hf Mem use?

Hf Mem is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hf Mem use?

About 832 tokens (SKILL.md is roughly 3.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hf Mem?

Skills that share tags, products or a category with Hf Mem: Qwen Mtp Gguf (R6410418/Jackrong-llm-finetuning-guide, 1.7k stars), Add Model (guoqingbao/xinfer, 334 stars), Huggingface LLM Trainer (waybarrios/opencode-power-pack, 533 stars) and Resolve (alexziskind1/model-shelf, 130 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hf Mem?

huggingface (a GitHub organization, an official publisher) maintains it in huggingface/skills, which has 11,151 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 8, 2026.

Source: huggingface/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Hf Mem

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

When to use?

What are the requirements?

How to run?

Examples

Files

Used in 4 other repositories

Compare with similar skills

Similar skills

More from huggingface/skills

Related

Questions about Hf Mem