hf-fetch-model

A Rust library and CLI for downloading HuggingFace models at maximum speed. Multi-connection parallel downloads, file filtering, checksum verification, retry — and a search command to find models before you download them.

Install

cargo install hf-fetch-model --features cli

Try it

$ hf-fm search mistral,3B,instruct
Models matching "mistral,3B,instruct" (by downloads):

  hf-fm mistralai/Ministral-3-3B-Instruct-2512           (159,700 downloads)
  hf-fm mistralai/Ministral-3-3B-Instruct-2512-BF16      (62,600 downloads)
  hf-fm mistralai/Ministral-3-3B-Instruct-2512-GGUF      (32,700 downloads)
  ...

$ hf-fm search mistralai/Ministral-3-3B-Instruct-2512 --exact
Exact match:

  hf-fm mistralai/Ministral-3-3B-Instruct-2512           (159,700 downloads)

  License:      apache-2.0
  Pipeline:     text-generation
  Library:      vllm
  Languages:    en, fr, es, de, it, pt, nl, zh, ja, ko, ar

$ hf-fm list-files mistralai/Ministral-3-3B-Instruct-2512 --preset safetensors
  File                                               Size      SHA256
  model-00001-of-00002.safetensors                 3.68 GiB    a1b2c3d4e5f6
  model-00002-of-00002.safetensors                 2.88 GiB    f6e5d4c3b2a1
  config.json                                        856 B     —
  ...
  7 files, 6.57 GiB total

$ hf-fm mistralai/Ministral-3-3B-Instruct-2512 --preset safetensors --dry-run
  Repo:     mistralai/Ministral-3-3B-Instruct-2512
  Revision: main

  File                                               Size      Status
  model-00001-of-00002.safetensors                 3.68 GiB    to download
  model-00002-of-00002.safetensors                 2.88 GiB    to download
  ...
  Total: 6.57 GiB (7 files, 0 cached, 7 to download)

  Recommended config:
    concurrency:        2
    connections/file:   8
    chunk threshold:  100 MiB

$ hf-fm mistralai/Ministral-3-3B-Instruct-2512 --preset safetensors
Downloaded to: ~/.cache/huggingface/hub/models--mistralai--Ministral-3-3B.../snapshots/...
  6.57 GiB in 18.2s (369.1 MiB/s)

Library quick start

let outcome = hf_fetch_model::download(
    "google/gemma-2-2b-it".to_owned(),
).await?;

println!("Model at: {}", outcome.inner().display());

Filter, progress, auth, and more via the builder — see Configuration.

Documentation

Topic
CLI Reference	All subcommands, flags, and output examples
Search	Comma filtering, `--exact`, model card metadata
Configuration	Builder API, presets, progress callbacks
Architecture	How hf-fetch-model relates to `hf-hub` and `candle-mi`
Diagnostics	`--verbose` output, `tracing` setup for library users
Changelog	Release history and migration notes

Used by

candle-mi — Mechanistic interpretability toolkit for transformer models

License

Licensed under either of Apache License, Version 2.0 or MIT License at your option.

Development

Exclusively developed with Claude Code (dev) and Augment Code (review)
Git workflow managed with Fork
All code follows CONVENTIONS.md, derived from Amphigraphic-Strict's Grit — a strict Rust subset designed to improve AI coding accuracy.

hf-fetch-model 0.8.2