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HuggingFace Model Downloader bodaay

huggingface
Use this command to install HuggingFace Model Downloader:
winget install --id=bodaay.hfdownloader -e

The HuggingFace Model Downloader is a utility tool for downloading models and datasets from the HuggingFace website. It offers multithreaded downloading for LFS files and ensures the integrity of downloaded models with SHA256 checksum verification.

The HuggingFace Model Downloader is a utility tool designed to streamline the process of downloading models and datasets from the HuggingFace platform. It simplifies access to machine learning resources by offering efficient and reliable retrieval mechanisms.

Key Features:

  • Multithreaded LFS File Downloads: Enhances download speeds for large files, making it easier to handle extensive model and dataset files.
  • SHA256 Checksum Verification: Ensures the integrity of downloaded models, confirming they are unchanged and valid.
  • Cross-Platform Compatibility: Operates seamlessly across various operating systems, including Linux, macOS, and Windows WSL2.
  • Configuration File Support: Allows users to set default values for command flags, enhancing customization and ease of use.
  • Download Resumption: Continues interrupted downloads without starting over, saving time and bandwidth.
  • HuggingFace Access Token Integration: Supports secure access to restricted models and datasets using tokens.

Audience & Benefit:

Ideal for researchers, data scientists, and developers working with machine learning models. This tool enables efficient retrieval of resources, ensuring reliability and integrity while handling large-scale downloads. Its flexibility and robust features make it a valuable asset in managing machine learning projects effectively.

The HuggingFace Model Downloader can be installed via winget, offering a straightforward setup process to integrate into your workflow seamlessly.

README

HuggingFaceModelDownloader · v2.0.0

Fast, resilient, resumable CLI (and Go library) for downloading models and datasets from the Hugging Face Hub—now with a clean flag set, a colorful TUI, structured JSON events, retry/backoff, and filesystems‑only resume (no progress files).

> v2.0.0 is a breaking redesign of the CLI and library. The old README summarized that this major version simplifies flags, adds dry‑run plans, verification options, multipart thresholding, and JSON output. This document is the definitive, up‑to‑date guide for v2.0.0.

Highlights

  • Resumable by default

    • LFS files: verified by SHA‑256 (when provided by the repo).
    • Non‑LFS files: verified by size.
    • Large files use multipart range downloads with per‑part resume.

  • Beautiful live TUI

    • Auto‑adapts to terminal width/height; smart truncation; per‑file bars, speeds, ETA.
    • Colorful when supported; graceful plain‑text fallback (TERM=dumb or NO_COLOR=1).

  • Robust + fast cancellation

    • Ctrl‑C (SIGINT) or SIGTERM aborts immediately across goroutines; second Ctrl‑C exits.

  • Structured progress events (--json) for CI/logging.

  • Practical controls

    • Overall concurrency and per‑file connection limits.
    • Retry with exponential backoff.
    • Verification policy for non‑LFS files: none | size | etag | sha256.
    • Dry‑run “plan” mode (table or JSON).

  • No progress/meta files

    • Skip decisions are made only from what’s on disk (checksums/sizes). Note: the previous README mentioned saving an .hfdownloader.meta.json. v2.0.0 no longer persists such files; resume is purely filesystem‑based.

Installation

From source (Go 1.21+)

git clone https://github.com/bodaay/HuggingFaceModelDownloader
cd HuggingFaceModelDownloader
go build -o hfdownloader .
# optional:
# go install .   # installs into your $GOBIN
Versions
2.0.0
1.4.2
Website
github.com
License
Last Updated
9/6/2025

Requirements

  • Go 1.21+
  • macOS / Linux / Windows (modern terminals support the live TUI; otherwise it falls back to plain text)

Quick start

# Public model
hfdownloader download TheBloke/Mistral-7B-Instruct-v0.2-GGUF -o ./Models

# Private or gated repo (requires token)
HF_TOKEN=xxxx hfdownloader download owner/private-model -o ./Models

# Filter LFS artifacts by name; append a subdir for each filter
hfdownloader download TheBloke/vicuna-13b-v1.3.0-GGML:q4_0,q5_0 \
  --append-filter-subdir -o ./Models -c 8 --max-active 3

# Dataset mode
hfdownloader download facebook/flores --dataset -o ./Datasets

# Plan only (no downloads), pretty-printed JSON
hfdownloader download TheBloke/Mistral-7B-Instruct-v0.2-GGUF:q4_0 --dry-run --plan-format json

Tip: You can include filters in REPO via owner/name:filter1,filter2 or pass -F, --filters.

CLI

hfdownloader download [REPO] [flags]
# REPO: owner/name  or  owner/name:filter1,filter2

Common flags

  • Destination

    • -o, --output Storage — base folder for downloads

  • What to fetch

    • -r, --repo (optional if REPO positional is present)
    • --dataset — treat repo as dataset instead of model
    • -b, --revision main — branch/tag/sha
    • -F, --filters — comma‑separated LFS name filters (q4_0,q5_0)
    • --append-filter-subdir — put each filter’s files under its own subfolder

  • Speed and parallelism

    • -c, --connections 8 — per‑file HTTP range connections
    • --max-active GOMAXPROCS — max concurrent files
    • --multipart-threshold 32MiB — only multipart files ≥ threshold

  • Reliability

    • --retries 4 — retry attempts per request/part
    • --backoff-initial 400ms, --backoff-max 10s
    • --verify size — non‑LFS verification: none | size | etag | sha256

  • Planning / logging

    • --dry-run — plan only (no downloads)
    • --plan-format table — table | json (with --dry-run)
    • --json — emit machine‑readable events
    • -q, --quiet — reduce console noise
    • -v, --verbose — more diagnostics

  • Auth & config

    • -t, --token — Hugging Face token (or HF_TOKEN env)
    • --config — path to JSON config (defaults to ~/.config/hfdownloader.json if present)

> The old README showed a larger flag surface and described resume/overwrite toggles and metadata persistence; v2.0.0 deliberately simplifies this—resume is always on, and skip decisions are based on your files only (no metadata saved).

Live TUI (default)

  • Header: repo, revision, dataset flag, output dir, connections, verification, retries.
  • Global progress bar with %, bytes, speed, ETA.
  • Per‑file rows: status (▶/✓/•/×), filename (middle‑ellipsis), bar, bytes, speed, ETA.
  • Auto‑adjusts to width/height; plain text fallback when colors/ANSI aren’t available.

Disable color: set NO_COLOR=1 or run in non‑TTY pipelines. JSON mode: --json bypasses the TUI for structured events (see below).

JSON events (for CI/logging)

The downloader emits typed events:

  • scan_start
  • plan_item (one per file; includes size and whether it’s LFS)
  • file_start
  • file_progress (bytes/total, periodic for multipart)
  • retry (attempt #, message)
  • file_done (includes message: "skip (...)" when a file is skipped)
  • error
  • done

Example:

{"time":"2025-09-05T18:42:10Z","event":"scan_start","repo":"owner/name","revision":"main","message":"scanning repo"}
{"time":"2025-09-05T18:42:11Z","event":"plan_item","path":"model-q4_0.gguf","total":4227858432,"repo":"owner/name","revision":"main"}
{"time":"2025-09-05T18:42:29Z","event":"file_done","path":"model-q4_0.gguf","repo":"owner/name","revision":"main"}
{"time":"2025-09-05T18:42:29Z","event":"done","message":"download complete (downloaded 1, skipped 12)","repo":"owner/name","revision":"main"}

> Skip lines: each file prints at most one “skip (…)” per run. Deduplication is enforced internally.

Resume & verification (how it decides to skip)

  • LFS files (SHA available) → compute local SHA‑256 and compare to the repo’s SHA.

    • If equal → skip (file_done with skip (sha256 match)).
    • If different (even if size matches) → re‑download.

  • Non‑LFS / SHA unknown → compare file size.

    • If equal → skip (skip (size match)).
    • If different → re‑download.

  • Multipart parts → each range part downloads to path.part-00, path.part-01, …; matching‑length parts are not re‑fetched and the file is assembled when all parts are present.

Cancellation & signals

  • SIGINT/SIGTERM: fast, cooperative cancellation—no new work is scheduled, all goroutines exit promptly, and ongoing HTTP calls are context‑bound.
  • SIGKILL (9): cannot be intercepted by any program; the OS terminates immediately.

Examples

Download GGUF variants into separate subfolders

hfdownloader download TheBloke/Mistral-7B-Instruct-v0.2-GGUF:q4_0,q5_0 \
  --append-filter-subdir -o ./Models --connections 8 --max-active 3

Stricter verification (non‑LFS)

hfdownloader download owner/name --verify etag

Datasets

hfdownloader download huggingface/awesome-dataset --dataset -o ./Datasets

Plan first, then run

hfdownloader download owner/name:q4_0 --dry-run --plan-format json
hfdownloader download owner/name:q4_0

Configuration file

If --config is not provided, the tool will read ~/.config/hfdownloader.json when present and use values as defaults (CLI flags still override).

Example:

{
  "output": "Storage",
  "connections": 8,
  "max-active": 3,
  "multipart-threshold": "256MiB",
  "verify": "size",
  "retries": 4,
  "backoff-initial": "400ms",
  "backoff-max": "10s",
  "token": "hf_xxx"
}

Library usage (Go)

package main

import (
  "context"
  "log"

  "github.com/bodaay/HuggingFaceModelDownloader/hfdownloader"
)

func main() {
  job := hfdownloader.Job{
    Repo:      "TheBloke/Mistral-7B-Instruct-v0.2-GGUF:q4_0",
    Revision:  "main",
    IsDataset: false,
    Filters:   []string{"q4_0"},
    // AppendFilterSubdir: true, // optional
  }

  cfg := hfdownloader.Settings{
    OutputDir:          "Storage",
    Concurrency:        8,
    MaxActiveDownloads: 3,
    MultipartThreshold: "256MiB",
    Verify:             "size",    // none|size|etag|sha256
    Retries:            4,
    BackoffInitial:     "400ms",
    BackoffMax:         "10s",
    Token:              "",        // or os.Getenv("HF_TOKEN")
  }

  progress := func(ev hfdownloader.ProgressEvent) {
    switch ev.Event {
    case "file_done":
      if strings.HasPrefix(ev.Message, "skip") {
        log.Printf("skip: %s (%s)", ev.Path, ev.Message)
      } else {
        log.Printf("done: %s", ev.Path)
      }
    case "retry":
      log.Printf("retry %s: attempt %d: %s", ev.Path, ev.Attempt, ev.Message)
    }
  }

  if err := hfdownloader.Download(context.Background(), job, cfg, progress); err != nil {
    log.Fatal(err)
  }
}

Events you can handle: scan_start, plan_item, file_start, file_progress, retry, file_done, error, done.

Troubleshooting

  • 401 Unauthorized Provide a token: -t TOKEN or HF_TOKEN=.... Some repos require auth/acceptance.
  • 403 Forbidden (terms) Visit the repo page and accept terms, then retry.
  • Range requests disabled Multipart falls back to a single GET automatically; downloads still work.
  • Slow throughput Increase --connections and --max-active gradually; ensure disk/FS and network can keep up.
  • Repeated “skip” lines v2.0.0 emits at most one “skip (…)” per file per run. If you still see duplicates, check for duplicate paths in the upstream tree or path collisions on Windows.

Why v2?

  • Cleaner mental model (one download command, sensible defaults).
  • Filesystem‑only resume—reliable and transparent; no “state” files to corrupt.
  • JSON events and a TUI that looks great everywhere.
  • Strong cancellation story for real‑world, long‑running downloads.

> The prior README’s CLI outline and examples helped guide this cleanup; this version documents the finalized v2 surface and behavior.

License

Apache‑2.0 (see LICENSE).

Acknowledgements

Thanks to the HF community and tooling ecosystem—this project tries to be a pragmatic drop‑in for everyday model & dataset fetching.