Skip to content

chore(deps): update dependency huggingface_hub to v1.13.0#180

Open
renovate[bot] wants to merge 1 commit intomainfrom
renovate/huggingface_hub-1.x
Open

chore(deps): update dependency huggingface_hub to v1.13.0#180
renovate[bot] wants to merge 1 commit intomainfrom
renovate/huggingface_hub-1.x

Conversation

@renovate
Copy link
Copy Markdown
Contributor

@renovate renovate Bot commented Mar 25, 2026 •
edited
Loading

ℹ️ Note

This PR body was truncated due to platform limits.

This PR contains the following updates:

Package Change Age Confidence
huggingface_hub ==1.4.1 → ==1.13.0 age confidence

Warning

Some dependencies could not be looked up. Check the Dependency Dashboard for more information.

Release Notes

huggingface/huggingface_hub (huggingface_hub)

v1.13.0: [v1.13.0] new CLI commands and formatting, and HF URI parsing

Compare Source

🖥️ New CLI commands: repo cards, file listings, and dataset leaderboards

This release adds three new CLI capabilities for exploring Hub content. hf models card, hf datasets card, and hf spaces card fetch the README of any repo and print it to stdout, with --metadata (YAML frontmatter as JSON) and --text (prose only) flags for splitting the card into its structured and unstructured parts. Calling hf models ls <repo_id>, hf datasets ls <repo_id>, or hf spaces ls <repo_id> now switches from listing repos to listing files inside that repo, with --tree, -R, -h, and --revision options mirroring the existing hf buckets ls behavior. And hf datasets leaderboard <dataset_id> surfaces model scores submitted to a benchmark dataset, making it easy to compare models by score from the terminal.

# Get model card metadata as JSON
hf models card google/gemma-4-31B-it --metadata --format json

# List files in a model repo (tree view with sizes)
hf models ls meta-llama/Llama-3.2-1B-Instruct --tree -h

# Show top 5 models on SWE-bench
hf datasets leaderboard SWE-bench/SWE-bench_Verified --limit 5

📚 Documentation: CLI guide

🚀 Manage Spaces from the CLI

Three new hf spaces subcommands bring full lifecycle control to the terminal. hf spaces pause and hf spaces restart stop or rebuild a Space (with --factory-reboot for a clean rebuild), and hf spaces settings lets you configure sleep time and hardware in one call. A companion hf spaces hardware command lists all available hardware flavors with pricing, so you can discover options before changing settings. Pause and restart include a confirmation prompt (-y to skip) since they tear down the running container.

# Pause a Space when not in use (not billed while paused)
hf spaces pause username/my-space

# Restart with a GPU
hf spaces settings username/my-space --hardware t4-medium --sleep-time 3600

# List available hardware options
hf spaces hardware

📚 Documentation: CLI guide — Spaces

🔃 hf update replaces the auto-update prompt

The blocking interactive Y/n auto-update prompt at CLI startup is gone. It was catching too many non-interactive contexts (CI runners, Homebrew post-install hooks, Jupyter notebooks) and hanging automation. In its place, a single yellow stderr warning suggests running hf update — a new command that detects how hf was installed (Homebrew, standalone installer, or pip) and runs the right upgrade command. Set HF_HUB_DISABLE_UPDATE_CHECK=1 to silence the startup check entirely, for example in offline CI.

hf update

📚 Documentation: CLI guide — Updating

✏️ Global output formatting for every command

The --format, --json, and -q / --quiet flags are now handled globally by the CLI framework instead of being declared individually on each command. This means every hf command automatically accepts them — no more per-command --format boilerplate, and the flags are properly documented in a dedicated "Formatting options" section in every --help page. --format auto (the default) picks human for interactive terminals and agent when invoked by an AI agent, making CLI output automatically suitable for both people and tools.

# JSON output for scripting
hf models ls --search bert --limit 2 --json | jq '.[].id'

# IDs only, one per line
hf collections ls --owner nvidia -q

📚 Documentation: CLI guide — Output formatting

🔗 Centralized hf:// URI parsing

A new parse_hf_uri function and HfUri dataclass provide a single source of truth for parsing hf://... strings across the library. Whether you reference a model, dataset, space, bucket, or file inside a repo, the parser handles all valid URI shapes — type prefixes, revisions, and paths — and rejects invalid ones with clear error messages. A companion parse_hf_mount / HfMount handles volume mount specifications (hf://...:/mnt:ro). Both are pure string parsers (no network calls) and round-trippable via .to_uri().

from huggingface_hub import parse_hf_uri, parse_hf_mount

parse_hf_uri("hf://datasets/namespace/my-dataset@refs/pr/3/train.json")

# HfUri(type='dataset', id='namespace/my-dataset', revision='refs/pr/3', path_in_repo='train.json')

parse_hf_mount("hf://buckets/my-org/my-bucket/sub/dir:/mnt:ro")

# HfMount(source=HfUri(type='bucket', id='my-org/my-bucket', ...), mount_path='/mnt', read_only=True)

📚 Documentation: HF URIs reference

🚀 Bucket transport for Jobs script upload

Local scripts uploaded by hf jobs uv run are now stored in a {namespace}/jobs-artifacts bucket and mounted into the job container at /data instead of being base64-encoded into an environment variable. The old bash -c + xargs + base64 -d pipeline was fragile and required manual shell quoting. Bucket transport is simpler, easier to debug, and supports write-back: jobs can persist output artifacts to /data/ since the mount is read-write. The base64 transport path has been fully removed with no fallback.

🖥️ CLI

  • [CLI] Print help when leaf command with required args is called without args by @​Wauplin in #​4135

🤖 Inference

📖 Documentation

🐛 Bug and typo fixes

🏗️ Internal

v1.12.2: [v1.12.2] Add DeepInfra support for Inference Providers

Compare Source

Full Changelog: huggingface/huggingface_hub@v1.12.1...v1.12.2

v1.12.1

Compare Source

v1.12.0: [v1.12.0] Unified CLI output, bucket search, and more

Compare Source

🖥️ Unified output format for hf buckets commands

All hf buckets commands now use the unified --format [auto|human|agent|json|quiet] flag and the out singleton for consistent, scriptable output. The previous --quiet and --format table|json flags have been replaced by a single --format option that works across create, list, info, delete, rm, move, and cp. Success messages use out.result(), detail views use out.dict(), and listings use out.table() with proper empty-results handling — making the buckets CLI consistent with the rest of the hf command suite.

# Quiet mode: print only bucket IDs
hf buckets list --format quiet

# JSON output for scripting
hf buckets create my-bucket --format json

# Agent-friendly structured output
hf buckets info username/my-bucket --format agent

📚 Documentation: Buckets guide · CLI guide

🪣 Search buckets by name

You can now filter buckets by name when listing them, both from the Python API and the CLI. Pass search="checkpoint" to list_buckets() or --search "checkpoint" to hf buckets list to find buckets matching a name pattern, without having to list and filter client-side.

# Filter buckets by name
hf buckets list --search "checkpoint"
# Filter buckets by name in Python
for bucket in list_buckets(search="checkpoint"):
    print(bucket.id)

📚 Documentation: Buckets guide · CLI guide

🖥️ CLI

🐛 Bug and typo fixes

🔧 Other QoL Improvements

🏗️ Internal

v1.11.0: [v1.11.0] Semantic Spaces search, Space logs, and more

Compare Source

🔍 Semantic search for Spaces

Discover Spaces using natural language. The new search_spaces() API and hf spaces search CLI use embedding-based semantic search to find relevant Spaces based on what they do - not just keyword matching on their name.

>>> from huggingface_hub import search_spaces

>>> results = search_spaces("remove background from photo")
>>> for space in results:
...     print(f"{space.id} (score: {space.score:.2f})")
briaai/BRIA-RMBG-1.4 (score: 0.87)

The same capability is available in the CLI:

$ hf spaces search "remove background from photo" --limit 3
ID                           TITLE                 SDK    LIKES STAGE   CATEGORY           SCORE
---------------------------- --------------------- ------ ----- ------- ------------------ -----
not-lain/background-removal  Background Removal    gradio 2794  RUNNING Image Editing      0.85 
briaai/BRIA-RMBG-2.0         BRIA RMBG 2.0         gradio 918   RUNNING Background Removal 0.84 
Xenova/remove-background-web Remove Background Web static 739   RUNNING Background Removal 0.81 
Hint: Use --description to show AI-generated descriptions.

# Filter by SDK, get JSON with descriptions
$ hf spaces search "chatbot" --sdk gradio --description --json --limit 1 | jq
[
  {
    "id": "BarBar288/Chatbot",
    "title": "Chatbot",
    "sdk": "gradio",
    "likes": 4,
    "stage": "RUNNING",
    "category": "Other",
    "score": 0.5,
    "description": "Perform various AI tasks like chat, image generation, and text-to-speech"
  }
]

📜 Programmatic access to Space logs

When a Space fails to build or crashes at runtime, you can now retrieve the logs programmatically — no need to open the browser. This is particularly useful for agentic workflows that need to debug Space failures autonomously.

>>> from huggingface_hub import fetch_space_logs

# Run logs (default)
>>> for line in fetch_space_logs("username/my-space"):
...     print(line, end="")

# Build logs — for BUILD_ERROR debugging
>>> for line in fetch_space_logs("username/my-space", build=True):
...     print(line, end="")

# Stream in real time
>>> for line in fetch_space_logs("username/my-space", follow=True):
...     print(line, end="")

The CLI equivalent:

$ hf spaces logs username/my-space              # run logs
$ hf spaces logs username/my-space --build      # build logs
$ hf spaces logs username/my-space -f           # stream in real time
$ hf spaces logs username/my-space -n 50        # last 50 lines

🖥️ CLI output standardization continues

This release continues the CLI output migration started in v1.9, bringing 11 more command groups to the unified --format flag. The old --quiet flags on migrated commands are replaced by --format quiet.

$ hf cache ls                          # auto-detect (human or agent)
$ hf cache ls --format json            # structured JSON
$ hf cache ls --format quiet           # minimal output, great for piping
$ hf upload my-model . .               # auto-detect (human or agent)

Confirmation prompts (e.g., hf cache rm, hf repos delete, hf buckets delete) are now mode-aware: they prompt in human mode, and require --yes in agent/json/quiet modes - no more hanging scripts.

Commands migrated in this release: collections, discussions, extensions, endpoints, webhooks, cache, repos, repo-files, download, upload, and upload-large-folder. Remaining commands (jobs, buckets, auth login/logout) will follow in a future release.

📦 Space volumes management from the CLI

A new hf spaces volumes command group lets you manage volumes mounted in Spaces directly from the command line — list, set, and delete using the familiar -v/--volume syntax.

# List mounted volumes
$ hf spaces volumes ls username/my-space
TYPE    SOURCE                MOUNT_PATH READ_ONLY
------- --------------------- ---------- ---------
model   gpt2                  /data      ✔
dataset badlogicgames/pi-mono /data2     ✔

# Set volumes
$ hf spaces volumes set username/my-space -v hf://buckets/username/my-bucket:/data
$ hf spaces volumes set username/my-space -v hf://models/username/my-model:/models

# Delete all volumes
$ hf spaces volumes delete username/my-space

🔧 More CLI improvements

hf auth token - Prints the current token to stdout, handy for piping into other commands:

$ hf auth token
hf_xxxx
Hint: Run `hf auth whoami` to see which account this token belongs to.

# Use it in a curl call
$ hf auth token | xargs -I {} curl -H "Authorization: Bearer {}" https://huggingface.co/api/whoami-v2

💔 Breaking change

model_name deprecated in list_models - Use search instead. Both were always equivalent (both map to ?search=... in the API), but now model_name emits a deprecation warning. Removal is planned for 2.0.

# Before
>>> list_models(model_name="gemma")

# After
>>> list_models(search="gemma")

The CLI is not affected - hf models ls already uses --search.

🔧 Other improvements

🐛 Bug fixes

📖 Documentation

🏗️ Internal

v1.10.2: [v1.10.2] Fix reference cycle in hf_raise_for_status

Compare Source

  • Fix reference cycle in hf_raise_for_status causing delayed object destruction by @​Wauplin in #​4092

Full Changelog: huggingface/huggingface_hub@v1.10.1...v1.10.2

v1.10.1: [v1.10.1] Fix copy file to folder

Compare Source

  • Fix copy file to folder (#​4075)
  • [CLI ]Improving a bit hf CLI discoverability (#​4079)
  • Support kernels in list_liked_repos (#​4078)

Full Changelog: huggingface/huggingface_hub@v1.10.0...v1.10.1

v1.10.0: [v1.10.0] Instant file copy and new Kernel repo type

Compare Source

📁 Instant file copy between Buckets and Repositories

This release introduces server-side file copy operations that let you move data between Hugging Face storage without downloading and re-uploading. You can now copy files from one Bucket to another, from a repository (model, dataset, or Space) to a Bucket, or between Buckets — all without bandwidth costs. Files tracked with Xet are copied directly by hash (no data transfer), while small text files not tracked with Xet are automatically downloaded and re-uploaded.

>>> from huggingface_hub import copy_files

# Bucket to bucket (same or different bucket)
>>> copy_files(
...     "hf://buckets/username/source-bucket/checkpoints/model.safetensors",
...     "hf://buckets/username/destination-bucket/archive/model.safetensors",
... )

# Repo to bucket
>>> copy_files(
...     "hf://datasets/username/my-dataset/processed/",
...     "hf://buckets/username/my-bucket/datasets/processed/",
... )

The same capability is available in the CLI:

# Bucket to bucket
>>> hf buckets cp hf://buckets/username/source-bucket/logs/ hf://buckets/username/archives/logs/

# Repo to bucket
>>> hf buckets cp hf://datasets/username/my-dataset/data/train/ hf://buckets/username/my-bucket/datasets/train/

Note that copying files from a Bucket to a Repository is not yet supported.

📚 Documentation: Buckets guide

⚛️ Introducing Kernel repositories

[!TIP]
For building, publishing, and using kernel repos, please use the dedicated kernels package.

The Hub now supports a new kernel repository type for hosting compute kernels. This release adds first-class (but explicitly limited) support for interacting with kernel repos via the Python API. Only a subset of methods are officially supported: kernel_info, hf_hub_download, snapshot_download, list_repo_refs, list_repo_files, and list_repo_tree. Creation and deletion are also supported but restricted to a small subset of allowed users and organizations on the Hub.

>>> from huggingface_hub import kernel_info
>>> kernel_info("kernels-community/yoso")
KernelInfo(id='kernels-community/yoso', author='kernels-community', downloads=0, gated=False, last_modified=datetime.datetime(2026, 4, 3, 22, 27, 25, tzinfo=datetime.timezone.utc), likes=0, private=False)

📚 Documentation: Repository guide

📖 Documentation

🐛 Bug and typo fixes

🏗️ Internal

v1.9.2: [v1.9.2] Fix set_space_volume / delete_space_volume return types

Compare Source

Full Changelog: huggingface/huggingface_hub@v1.9.1...v1.9.2

v1.9.1: [v1.9.1] Fix: set_space_volumes sending bare array instead of object

Compare Source

Full Changelog: huggingface/huggingface_hub@v1.9.0...v1.9.1

v1.9.0: [v1.9.0] Agent-Aware CLI, Spaces Volumes, and more

Compare Source

🚀 Spaces Volumes: Mount Models, Datasets, and Buckets Directly

Hugging Face Spaces now support mounting volumes, giving your Space direct filesystem access to models, datasets, and storage buckets. This replaces the deprecated persistent storage feature.

from huggingface_hub import HfApi, Volume

api = HfApi()
api.set_space_volumes(
    repo_id="username/my-space",
    volumes=[
        Volume(type="model", source="username/my-model", mount_path="/models", read_only=True),
        Volume(type="bucket", source="username/my-bucket", mount_path="/data"),
    ],
)

Volumes can also be set at creation time via create_repo(space_volumes=...) and duplicate_repo(space_volumes=...), and from the CLI with the --volume / -v flag:

# Create a Space with volumes mounted
hf repos create my-space --type space --space-sdk gradio \
    -v hf://gpt2:/models -v hf://buckets/org/b:/data

# Duplicate a Space with volumes
hf repos duplicate org/my-space my-space --type space \
    -v hf://gpt2:/models -v hf://buckets/org/b:/data

🤖 The hf CLI Now Auto-Detects AI Agents and Adapts Its Output

AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, ...) increasingly use the hf CLI to interact with the Hub. Until now, the output was designed for humans - ANSI colors, padded tables, emoji booleans, truncated cells - making it hard for agents to parse reliably.

Starting with v1.9, the CLI automatically detects when it's running inside an agent and adapts its output: no ANSI, no truncation, tab-separated tables, compact JSON, full timestamps. No configuration needed - it just works. This is only a first step toward making the hf CLI the primary entry point to the Hugging Face Hub for AI agents!

Agent mode is auto-detected but you can also force a mode explicitly with --format:

hf models ls --limit 5                  # auto-detect
hf models ls --limit 5 --format agent   # force agent-friendly output
hf models ls --limit 5 --format json    # structured JSON
hf models ls --limit 5 --format quiet   # IDs only, great for piping

Here's what an agent sees compared to a human:

hf auth whoami


# Human
✓ Logged in
  user: Wauplin
  orgs: huggingface, awesome-org

# Agent
user=Wauplin orgs=huggingface,awesome-org

# JSON
{"user": "Wauplin", "orgs": ["huggingface", "awesome-org"]}

hf models ls --author google --limit 3


# Human
ID                         DOWNLOADS TRENDING_SCORE
-------------------------- --------- --------------
google/embeddinggemma-300m 1213145   17            
google/gemma-3-4b-it       1512637   16            
google/gemma-3-27b-it      988618    12   

# Agent (TSV, no truncation, no ANSI)
id      downloads       trending_score
google/embeddinggemma-300m      1213145 17
google/gemma-3-4b-it    1512637 16
google/gemma-3-27b-it   988618  12

hf models info google/gemma-3-27b-it


# Human — pretty-printed JSON (indent=2)
{
  "id": "google/gemma-3-27b-it",
  "author": "google",
  ...
}

# Agent — compact JSON (~40% fewer tokens)
{"id": "google/gemma-3-27b-it", "author": "google", "card_data": ...}

Commands migrated so far: hf models ls|info, hf datasets ls|info|parquet|sql, hf spaces ls|info, hf papers ls|search|info, hf auth whoami. More commands will be migrated soon

🧩 Install Agent Skills from the Hugging Face Marketplace

The hf skills add command now supports installing skills directly from the Hugging Face skills marketplace (https://github.com/huggingface/skills) - pre-built tools that give AI agents new capabilities.

# Install a marketplace skill
hf skills add gradio

# Install with Claude Code integration
hf skills add huggingface-gradio --claude

# Upgrade all installed skills
hf skills upgrade

🔧 More CLI Improvements

🔧 Other Improvements

🐛 Bug Fixes

📖 Documentation

🏗️ Internal

v1.8.0: [v1.8.0] Mounted volumes on Jobs, complete papers CLI, and more

Compare Source

🚀 Jobs can now mount volumes

Jobs can now access Hugging Face repositories (models, datasets, Spaces) and Storage Buckets directly as mounted volumes in their containers. This enables powerful workflows like running queries directly against datasets, loading models without explicit downloads, and persisting training checkpoints to buckets.

from huggingface_hub import run_job, Volume

job = run_job(
    image="duckdb/duckdb",
    command=["duckdb", "-c", "SELECT * FROM '/data/**/*.parquet' LIMIT 5"],
    volumes=[
        Volume(type="dataset", source="HuggingFaceFW/fineweb", mount_path="/data"),
    ],
)
hf jobs run -v hf://datasets/HuggingFaceFW/fineweb:/data duckdb/duckdb duckdb -c "SELECT * FROM '/data/**/*.parquet' LIMIT 5"

📖 Papers CLI is now complete

The hf papers command now has full functionality: search papers by keyword, get structured JSON metadata, and read the full paper content as markdown. The ls command is also enhanced with new filters for week, month, and submitter.

# Search papers
hf papers search "vision language"

# Get metadata
hf papers info 2601.15621

# Read as markdown
hf papers read 2601.15621

🖥️ CLI repo ID shorthand

You can now use repo ID prefixes like spaces/user/repo, datasets/user/repo, and models/user/repo as a shorthand for user/repo --type space. This works automatically for all CLI commands that accept a --type flag.

# Before
hf download user/my-space --type space
hf discussions list user/my-dataset --type dataset

# After
hf download spaces/user/my-space
hf discussions list datasets/user/my-dataset

🔧 More repo visibility options

Repositories can now be created or updated with explicit visibility settings (--public, --protected) alongside the existing --private flag. This adds a visibility parameter to HfApi.create_repo, update_repo_settings, and duplicate_repo, with --protected available for Spaces only.

Protected Spaces allow for private code while being publicly accessible.

🖥️ CLI

🔧 Other QoL Improvements

🐛 Bug and typo fixes

  • Use module logger consistently and narrow bare except clauses by @​mango766 in [#​3924](https:

✂ Note

PR body was truncated to here.

Configuration

📅 Schedule: (in timezone America/New_York)

  • Branch creation
    • "after 9am and before 5pm every weekday"
  • Automerge
    • At any time (no schedule defined)

🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.

♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.

🔕 Ignore: Close this PR and you won't be reminded about this update again.

  • If you want to rebase/retry this PR, check this box

This PR was generated by Mend Renovate. View the repository job log.

@renovate renovate Bot added dependencies Pull requests that update a dependency file renovate labels Mar 25, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from d371cfa to c217995 Compare March 25, 2026 16:46
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.7.2 chore(deps): update dependency huggingface_hub to v1.8.0 Mar 25, 2026
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.8.0 chore(deps): update dependency huggingface_hub to v1.9.0 Apr 3, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch 2 times, most recently from 9a71c54 to 7c0eb2a Compare April 7, 2026 14:53
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.9.0 chore(deps): update dependency huggingface_hub to v1.9.1 Apr 7, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from 7c0eb2a to 2fb4a10 Compare April 8, 2026 10:09
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.9.1 chore(deps): update dependency huggingface_hub to v1.9.2 Apr 8, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from 2fb4a10 to 3533357 Compare April 9, 2026 13:27
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.9.2 chore(deps): update dependency huggingface_hub to v1.10.0 Apr 9, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from 3533357 to 46ae470 Compare April 9, 2026 16:53
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.10.0 chore(deps): update dependency huggingface_hub to v1.10.1 Apr 9, 2026
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.10.1 chore(deps): update dependency huggingface_hub to v1.10.2 Apr 14, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch 2 times, most recently from 60f1705 to bd7d79b Compare April 16, 2026 17:03
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.10.2 chore(deps): update dependency huggingface_hub to v1.11.0 Apr 16, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from bd7d79b to 735c98b Compare April 24, 2026 14:35
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.11.0 chore(deps): update dependency huggingface_hub to v1.12.0 Apr 24, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from 735c98b to f0b9736 Compare April 29, 2026 16:28
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.12.0 chore(deps): update dependency huggingface_hub to v1.12.2 Apr 29, 2026
@renovate renovate Bot force-pushed the renovate/huggingface_hub-1.x branch from f0b9736 to 21bdb11 Compare April 30, 2026 16:42
@renovate renovate Bot changed the title chore(deps): update dependency huggingface_hub to v1.12.2 chore(deps): update dependency huggingface_hub to v1.13.0 Apr 30, 2026
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Reviewers

No reviews

Assignees

No one assigned

Labels

dependencies Pull requests that update a dependency file renovate

Projects

None yet

Milestone

No milestone

Development

Successfully merging this pull request may close these issues.

0 participants