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fix(deps): update dependency huggingface-hub to v2 - #345

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fix(deps): update dependency huggingface-hub to v2#345
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This PR contains the following updates:

Package Type Update Change OpenSSF
huggingface-hub project.dependencies major ==1.28.0 → ==2.3.0 OpenSSF Scorecard

Release Notes

huggingface/huggingface_hub (huggingface-hub)

v2.3.0: [v2.3.0] Bucket live-follow, faster HfFileSystem listings and more

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🔄 Keep Bucket listings fresh with live_follow=True

HfFileSystem caches directory listings, so files added to a Bucket by another process did not show up until you called invalidate_cache(). With live_follow=True, HfFileSystem opens one background connection per listed Bucket to receive its file changes from the Hub. When a change arrives, it removes the cached listings it affects.

>>> from huggingface_hub import HfFileSystem
>>> hffs = HfFileSystem(live_follow=True)
>>> hffs.ls("buckets/my-username/my-bucket/data", detail=False)  # starts following that bucket
>>> # ... another process uploads a file to the bucket ...
>>> hffs.ls("buckets/my-username/my-bucket/data", detail=False)  # refreshed as changes arrive
['buckets/my-username/my-bucket/data/train.csv', 'buckets/my-username/my-bucket/data/new-file.csv']

It also works through fsspec with fsspec.filesystem("hf", live_follow=True), and through the storage_options argument of libraries such as pandas and pyarrow. The option is off by default because it keeps a connection open for each followed Bucket. It only affects listings and metadata (ls, info, exists, glob, ...), because reading a file always fetches its content from the Hub. It is not available for model, dataset and Space repos: use refresh=True to see a new commit.

🚀 HfFileSystem lists large repos in parallel

Recursive listings such as find and glob used to be slow on large repos. The Hub returns a repo's file tree 1000 entries at a time, and each page can only be requested after the previous one has arrived. Listing datasets/allenai/objaverse (~800k files) took ~800 requests in a row, about 13 minutes.

HfFileSystem now splits recursive listings by sub-directory and lists them in parallel, with almost the same number of requests. A sub-tree that fits in a single page is never split. maxdepth is now applied during the listing, so the Hub only returns the levels you ask for.

datasets/allenai/objaverse before after
find(), 798,924 files 801 requests, 776 s 807 requests, 19.7 s
find(maxdepth=2), 328 entries 801 requests, 776 s 6 requests, 1.5 s 
>>> from huggingface_hub import hffs
>>> files = hffs.glob("datasets/allenai/objaverse/**/*.glb", maxdepth=3)

The new max_workers argument of HfFileSystem sets the number of concurrent requests. It defaults to 16. Set it to 1 to list sequentially like before.

📎 Attach images and videos to discussions and PRs

The new HfApi.upload_attachment(path) uploads an image, video or audio file and returns its URL, which you can embed in a discussion, PR description or comment. Before, this required calling an undocumented Hub endpoint by hand.

>>> from huggingface_hub import HfApi
>>> api = HfApi()
>>> url = api.upload_attachment("screenshot.png")
>>> api.comment_discussion("username/repo-name", 5, f"Here is the fix:\n\n![screenshot]({url})")

On the CLI, hf discussions create (including --pr), comment and edit take a repeatable --attach FILE[#alt text] option. If the body already references the file as ![alt](./file), that reference is replaced with the uploaded URL. Other files are added at the end of the body, the same way the Hub web editor does it.

$ hf discussions create celinah/hfh-attach-test --title "Fix rendering" --pr \
    --body "Before: ![Before the fix](./before.png)" --attach ./before.png --attach "./after.png#After the fix"
num=1 url=https://huggingface.co/celinah/hfh-attach-test/discussions/1 ref=refs/pr/1

$ hf discussions info celinah/hfh-attach-test 1 --format json | jq -r '.events[0].content'
Before: ![Before the fix](https://cdn-uploads.huggingface.co/production/uploads/6192895f3b8aa351a46fadfd/QdFSiYU0Plm7GM3kGSipw.png)

![After the fix](https://cdn-uploads.huggingface.co/production/uploads/6192895f3b8aa351a46fadfd/efw80nbXnJzUL5-rJXLo0.png)

🧩 Read every safetensors shard header in one request

get_safetensors_metadata reads the header of each shard of a sharded model separately. The new get_sharded_safetensors_metadata gets all of them from the Hub in a single request and returns the same SafetensorsRepoMetadata. It only reads the main revision. get_safetensors_metadata is unchanged.

>>> from huggingface_hub import get_sharded_safetensors_metadata
>>> metadata = get_sharded_safetensors_metadata("HuggingFaceH4/zephyr-7b-beta")
>>> len(metadata.files_metadata)
8
  • [Safetensors] Add get_sharded_safetensors_metadata to get every shard header in one request by @​mishig25 in #​5159

🔒 Access requests on gated repos that hide requester identity

Owners of gated repos can now choose not to share the username and/or email of the people requesting access. On those repos, list_pending_access_requests (and the accepted and rejected variants) failed with a KeyError. Each AccessRequest now has a request_id, and accept_access_request, reject_access_request and cancel_access_request accept request_id= instead of user.

>>> from huggingface_hub import list_pending_access_requests, accept_access_request
>>> for request in list_pending_access_requests("my-org/gated-model"):
...     accept_access_request("my-org/gated-model", request_id=request.request_id)

[!NOTE]
AccessRequest.username and AccessRequest.fullname are now typed str | None. They are only None on repos that hide usernames, where listing requests used to fail anyway, but type checkers may flag code that assumes a str.

🛡️ create_commit no longer deletes files you re-add in the same commit

create_commit skips adds and copies whose content is already on the Hub. When the same commit also deleted that path or its parent folder, only the delete was sent, and the file was removed from the repo without any error. This affected deleting a folder and pushing the same files back in one commit, and had been happening since v0.24. Those adds are now kept.

api.create_commit(repo_id, operations=[
    CommitOperationDelete("x/", is_folder=True),
    CommitOperationAdd("x/a.txt", b"keep me\n"),  # unchanged on the Hub
], commit_message="Reset x/")

# before: x/a.txt is deleted
# after:  x/a.txt is kept

💼 hf jobs run keeps streaming logs and shows queue status

hf jobs run stopped printing logs when the log stream ended before the Job did, and crashed after a few dropped connections. It now reconnects until the Job reaches a final stage. Ctrl+C used to stop the logs while the CLI kept waiting silently for the Job to end. It now exits right away and tells you that the Job is still running and how to follow or cancel it.

hf jobs run before and after: logs keep streaming and Ctrl+C exits with a hint

While a Job waits for hardware, hf jobs run, hf jobs uv run and hf jobs rerun printed nothing, so a queued Job looked like a stuck CLI. They now show the Hub's status message and how long the Job has been waiting, in interactive terminals only:

hf jobs run showing the scheduling status while the Job waits for hardware

🐍 Python 3.15 support

huggingface_hub now officially supports Python 3.15 and is tested on it in CI. No code changes were needed. Python 3.10 is still the minimum version.

🤖 Inference

  • [Inference] Don't keep non-streaming responses alive in InferenceClient by @​hanouticelina in #​5197. A reused InferenceClient kept every non-streaming response in memory until close(). With 30 calls and a 1 MB prompt, that was 30 MB.
  • [Inference] Run provider get_response in a thread in AsyncInferenceClient by @​hanouticelina in #​5200. Queue-based providers (fal-ai, wavespeed, together video, zai-org) wait for results with blocking calls, which froze the event loop for the whole job.
  • [Inference] Raise InferenceTimeoutError on httpx timeouts by @​hanouticelina in #​5150. timeout now raises InferenceTimeoutError as documented, instead of the raw httpx timeout error.

🖥️ CLI

  • [Cache] Show unreferenced shared blobs in hf cache ls by @​hanouticelina in #​5148. Files left behind when an older huggingface_hub version deletes a repo now show up as a hint pointing to hf cache prune.
  • [CLI] Fix hf skills add when .claude/skills links to .agents/skills by @​hanouticelina in #​5204

🔧 Other QoL improvements

🐛 Bug and typo fixes

  • fix(kernels): allow uploads and commits to kernel repos by @​tengomucho in #​5233
  • [HfApi] Respect custom endpoint in webhooks, access requests and user APIs by @​hanouticelina in #​5149. With HfApi(endpoint=...), 20 methods (webhooks, access requests, user and org info, followers, members) were sent to huggingface.co with the instance's token. Setups using HF_ENDPOINT were not affected.
  • [HfFileSystem] Fix find/glob skipping folders that share a name prefix by @​hanouticelina in #​5147. Once a listing was cached, find() and glob() could silently skip folders such as images-ar next to images.
  • [HfFileSystem] Fix glob crash when the parent listing is outdated by @​hanouticelina in #​5237. Since v2.2.0, Dataset.push_to_hub("buckets/...") into a new bucket failed with FileNotFoundError after uploading the data files.
  • [Download] Skip the cached tree listing in offline mode by @​hanouticelina in #​5199. With HF_HUB_OFFLINE=1, hf_hub_download at a pinned commit could delete the existing file in local_dir instead of returning it.
  • [Download] Report outdated local files as downloads in dry runs by @​hanouticelina in #​5219
  • [Repocard] Read templates and metadata as UTF-8 by @​hanouticelina in #​5198. Fixes a UnicodeDecodeError when the process runs with the C locale, which broke checkpoint saving in TRL.
  • [Repocard] Ignore a UTF-8 BOM when reading README metadata by @​hanouticelina in #​5220. metadata_update on a README saved with a BOM added a second metadata block, and the Hub lost the original metadata.

📖 Documentation

🏗️ Internal

v2.2.0: [v2.2.0] hf jobs stats snapshots, download and HfFileSystem fixes

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A small release this week, mostly bug fixes and quality-of-life improvements. hf jobs stats now returns right away instead of streaming forever, concurrent downloads reliably use hf_xet, and HfFileSystem caching is more predictable. Two behavior changes are listed under Breaking changes.

📊 hf jobs stats prints a snapshot by default

hf jobs stats used to stream metrics until the job finished, so scripts and agents calling it on a running job hung until their own timeout. It now prints the latest sample of each job once and exits, like hf jobs logs and hf spaces logs. Use -f/--follow for the previous live view. Snapshot output also supports --format json|agent|quiet, which outputs the raw API metrics.

On the Python side, HfApi.fetch_job_metrics gets the same follow parameter as fetch_job_logs. It defaults to False and returns only the current sample. Pass follow=True to stream until the job completes.

>>> hf jobs stats 6ac3bd9afbc85ba6823a9ad4
JOB ID                CPU % NUM CPU MEM % MEM USAGE      NET I/O         GPU UTIL % GPU MEM % GPU MEM USAGE
--------------------- ----- ------- ----- -------------- --------------- ---------- --------- -------------
6ac3bd9afbc85ba682... 0%    2.0     0.01% 1.0MB / 16.0GB 0.0bps / 0.0bps N/A        N/A       N/A
Hint: Use `hf jobs stats -f celinah/6ac3bd9afbc85ba6823a9ad4` to follow live stats.

# Stream live stats until the job completes
>>> hf jobs stats -f 6ac3bd9afbc85ba6823a9ad4
>>> from huggingface_hub import fetch_job_metrics
>>> for metrics in fetch_job_metrics(job_id=job.id, follow=True):
...     print(metrics)

Other Jobs fixes in this release: hf jobs logs and hf spaces logs without -f no longer hang while the job keeps printing, hf jobs stats no longer fails when one of the requested jobs has finished, and hf jobs stats --json prints [] when no job is running.

📚 Documentation: Jobs guide

⚡ Concurrent downloads always use hf_xet

In a fresh process, the first concurrent hf_hub_download calls could read a placeholder version for hf_xet while another thread was still looking it up. Those calls treated hf_xet as missing and downloaded through the plain HTTP path. This mostly affected parallel downloads such as snapshot_download, where some of the files skipped Xet. The version lookup is now cached only once it is resolved, so every download sees the real value.

📂 HfFileSystem cache fixes

Three fixes to how HfFileSystem caches listings and missing paths:

  • ls() on a newly created empty bucket returns an empty list instead of raising FileNotFoundError.
  • Directory listings are now replaced in the cache instead of appended to. Before, ls() after find() or ls(refresh=True) could return duplicate entries, refresh=True kept deleted files, and listing a single bucket file cached it as the whole folder's listing.
  • exists(path, refresh=True) and invalidate_cache(path) now clear cached "not found" results. Before, a repo, branch or bucket created in the same process stayed missing until a full invalidate_cache().
>>> fs.exists(repo_id)
False
>>> api.create_repo(repo_id)
>>> fs.exists(repo_id, refresh=True)  # was False before this release
True

💔 Breaking changes

  • hf jobs stats and HfApi.fetch_job_metrics return a single snapshot by default instead of streaming until the job completes. Use -f/--follow or follow=True to keep the previous behavior. See the section above (#​5090).

  • load_torch_model now raises FileNotFoundError instead of ValueError when the checkpoint path does not exist, and model_index_to_eval_results raises ValueError on an empty list (#​5063).

  • [Bugfix] Fix wrong exception type and unbound variable guard by @​vector15-05 in #​5063

🖥️ CLI

  • [CLI] Don't glob-expand arguments on Windows by @​hanouticelina in #​5117. On Windows, quoted patterns such as --exclude ".venv/**" or --include "*.json" were expanded into local file names before reaching the command. hf download <repo> --include "*.json" in a folder containing a .json file silently downloaded nothing.
  • [CLI] Read --env-file / --secrets-file as UTF-8 and strip the BOM by @​hanouticelina in #​5066
  • [CLI] Upload existing paths with glob characters as-is in hf upload by @​Ganesh2325 in #​5059

🔧 Other QoL improvements

  • [Download] Warn when allow/ignore patterns match no files in snapshot_download by @​Ad1th in #​5067
  • [Cache] Speed up delete_revisions with a set lookup by @​hanouticelina in #​5118. Planning hf cache prune / hf cache rm no longer scales quadratically with the number of files per revision.
  • [Setup] Install hf-xet on Windows ARM64 by @​angt in #​5074

🐛 Bug and typo fixes

📖 Documentation

🏗️ Internal

v2.1.1

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[CLI] Rename 'hf spaces zero-gpu-quota' to 'hf spaces zero-gpu quota'- #​5055

Full Changelog: huggingface/huggingface_hub@v2.1.0...v2.1.1

v2.1.0: [v2.1.0] Better Jobs tooling, ZeroGPU quota tracking, and revamped Model Catalog

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📊 Jobs: retries, rescheduling, and port exposure

Hugging Face Jobs get a batch of quality-of-life improvements this release. Jobs can now retry automatically on failure with the new attempts parameter, and you can start a fresh Job from an existing Job's saved spec (including secrets and hardware settings) with rerun_job / hf jobs rerun. Scheduled Jobs can be rescheduled — change the cron expression or preset without recreating the Job — via update_scheduled_job_schedule / hf jobs scheduled reschedule. Finally, you can now expose ports on Jobs: use expose for token-protected access and expose_public for unauthenticated access, both at creation time and on a running Job with update_job_expose / hf jobs expose.

# Retry a job up to 2 times on failure, and rerun it later from its saved spec
>>> hf jobs run --attempts 3 --detach python:3.12 python train.py
>>> hf jobs rerun <job_id>

# Reschedule a scheduled job to run every day at 9:00
>>> hf jobs scheduled reschedule <scheduled_job_id> "0 9 * * 1"

# Expose ports on a running Job (8000 token-protected, 9000 public)
>>> hf jobs expose <job_id> 8000 --public 9000

📚 Documentation: Jobs guide

🤗 Track your ZeroGPU quota

The Hub now exposes a ZeroGPU quota endpoint, and huggingface_hub wraps it with a new HfApi.get_zero_gpu_quota() method returning a ZeroGpuQuota dataclass (values in GPU-seconds). This is particularly useful for apps, MCP servers and agents built on top of ZeroGPU Spaces: check how much quota is left and when it resets, and warn your users before they hit the daily limit. The same information is available from the CLI with hf spaces zero-gpu-quota, which also prints a hint to purchase credits when the quota is running low.

>>> from huggingface_hub import get_zero_gpu_quota
>>> quota = get_zero_gpu_quota()
ZeroGpuQuota(base=2400, remaining=1810, resets_at=datetime.datetime(2026, 9, 30, 9, 12, 3, tzinfo=datetime.timezone.utc), overquota_used=0)
>>> hf spaces zero-gpu quota
✓ ZeroGPU quota (in GPU-seconds)
  remaining: 1810
  base: 2400
  resets_at: 2026-09-30T18:12:03+00:00
  overquota_used: 0
  • [Spaces] Add get_zero_gpu_quota and hf spaces zero-gpu-quota by @​Wauplin in #​5040
  • [CLI] Rename 'hf spaces zero-gpu-quota' to 'hf spaces zero-gpu quota'- #​5055 [Shipped as part of v2.1.1]

📚 Documentation: Manage your Space guide

⚡ HfFileSystem.get_file downloads Xet files with hf_xet

HfFileSystem.get_file now downloads Xet-backed files through hf_xet (the same code path as hf_hub_download) when writing to a local path, letting hf_xet write directly to disk instead of going through Python. It reuses the Xet hash already returned by info() (part of the tree listing), so no extra HTTP call is needed. This mostly benefits non-streaming datasets loads from hf://buckets/... paths: benchmarks on HF Jobs show get_file dropping from ~120s to ~7s on a 2 GB parquet file, and load_dataset("hf://buckets/...") from ~130s to ~17s. The classic HTTP path is still used for non-Xet files, when hf_xet is not installed, or when writing to a file-like object. As a side effect, a missing remote file no longer leaves an empty local file behind.

🧠 Inference Endpoints: Model Catalog migrates to the new v1 API

The catalog methods now use the new /api/v1/catalog API. list_inference_catalog returns InferenceCatalogModel dataclasses with their tested deployment recipes (hardware + engine combinations), and takes server-side filters (accelerator, engine, license, task, search, limit). create_inference_endpoint_from_catalog can deploy an exact recipe with the new recipe_id and gguf_file arguments. The CLI follows suit: hf endpoints catalog ls prints one row per recipe and supports the filters, while hf endpoints catalog deploy gains --recipe and --gguf-file.

>>> hf endpoints catalog ls --engine vllm --task text-generation --search llama --limit 10
REPO_ID                             TASK               LICENSE    ACCELERATOR ENGINE   GGUF_FILE                     RECIPE_ID
----------------------------------- ------------------ ---------- ----------- -------- ----------------------------- -------------------------
meta-llama/Llama-3.1-8B-Instruct    text-generation    Llama 3.1  gpu         vllm                                   sizzling-biryani-g4xsi1ac
bartowski/QwQ-32B-Preview-GGUF      text-generation    Apache 2.0 gpu         llamacpp QwQ-32B-Preview-Q8_0.gguf     baked-orange-m863gx7d

📚 Documentation: Inference Endpoints guide

🔒 Sandboxes require scoped credentials

Sandbox security is tightened in this release. Pooled sandboxes with missing, empty or malformed capability tokens are now refused instead of silently substituting the host-management credential, and the client is pinned to sbx-server 0.7.0, which removes host-token acceptance on per-sandbox routes entirely. Older pool hosts that do not provide scoped tokens must be upgraded/recycled: new clients cannot reach legacy hosts and legacy clients cannot reach new sandboxes (documented, accepted breaking change). The sandbox concepts and guides have been updated to describe the strict behavior, including how to safely use proxy_headers with external HTTP clients (disable redirects!).

💔 Breaking Change

  • [Buckets] Make include/exclude patterns case-sensitive on all platforms by @​Wauplin in #​5007

[!NOTE]
The Inference Endpoints catalog migration (#​4928) and the Sandbox credential changes (#​4782, #​5028) are breaking changes detailed in their highlight sections above.

🖥️ CLI

🔧 Other QoL Improvements

🐛 Bug and typo fixes

📖 Documentation

🏗️ Internal

v2.0.0: [v2.0.0] The httpx2 release

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See MIGRATION GUIDE in docs.

💔 Breaking Change: HTTP stack moves to httpx2

See migration plan in #​4802 .

huggingface_hub v2.0 replaces its HTTP dependency with httpx2: clients and transport exceptions now come from httpx2/httpcore2 instead of httpx/httpcore. Custom client factories (via set_client_factory / set_async_client_factory) and any except clauses catching transport errors must use httpx2 types. For code that must support both v1.x (starting with v1.30.0) and v2.x, import the HTTP module from huggingface_hub.utils:

from huggingface_hub.utils import get_session, httpx

try:
    response = get_session().get("https://huggingface.co/api/models/gpt2")
    response.raise_for_status()
except httpx.HTTPError:
    ...

Note that httpx2 uses the operating system's certificate trust store by default (custom CA bundles via SSL_CERT_FILE / SSL_CERT_DIR still work), logging configuration should target the httpx2 and httpcore2 loggers, and the oauth extra now requires authlib>=1.8.0.

💔 Breaking Change: deprecated APIs are removed

This release also removes all APIs deprecated in 1.x:

  • upload_large_folder / HfApi.upload_large_folder → use upload_folder
  • duplicate_space → use duplicate_repo
  • request_space_storage / delete_space_storage → use the volume APIs (set_space_volumes, delete_space_volumes)
  • repo_type_and_id_from_hf_id → use parse_hf_uri
  • InferenceEndpointType.PROTECTED → use AUTHENTICATED (create_inference_endpoint(type="protected") now raises ValueError)
  • list_models(model_name=...) → use list_models(search=...)
  • create_repo / duplicate_repo(space_storage=...) → use space_volumes
  • text_generation(stop_sequences=...) → use stop
  • Boolean InferenceClient(token=...) → pass a token string or None

On the CLI side, the following entry points and options are gone: huggingface-cli (use hf), hf repo and hf repo-files delete (use hf repos and hf repos delete-files), hf upload-large-folder (use hf upload), hf repos create/duplicate --storage (use --volume), hf jobs ps and hf jobs scheduled ps -f/--filter (use --status/--label), and hf skills add/update --claude (Claude Code installation is now automatic).

A migration guide covering all of this is available at https://github.com/huggingface/huggingface_hub/blob/main/docs/source/en/concepts/migration_v2.md.

🏗️ Internal

v1.33.0: [v1.33.0] Better UX on large uploads and simpler skills installs

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📤 See progress while large Xet uploads validate

Very large Xet uploads used to sit silently between "Uploading" and "Committing" while shards were being finalized, which could take a long time with no feedback. The upload live display now shows a dedicated Validating bar — reported as a percentage instead of opaque internal validation-entry counts — both in the upload_folder display and in XetUploadProgressReporter (used by upload_file, create_commit and bucket uploads). This requires hf-xet>=1.6.0.

🧩 Skills are now installed for every agent by default

hf skills add no longer requires a special flag for Claude Code. The skill is now always installed to .agents/skills (or ~/.agents/skills with -g) and symlinked into .claude/skills (honoring CLAUDE_CONFIG_DIR when set), so a single command covers Claude Code, Codex, Cursor, OpenCode, Pi and any other agent that loads skills from .agents/skills. The --claude flag is deprecated: it still works as a no-op but prints a warning, and --dest keeps installing only to the directory you provide. hf skills update refreshes both roots the same way. Along the way, CLAUDE_CONFIG_DIR is now properly honored everywhere (it was previously ignored, which left skills invisible to relocated Claude Code installs).

# works with Claude Code, Codex, Cursor, OpenCode, Pi and any agent that loads skills from `.agents/skills`
hf skills add

📚 Documentation: CLI guide

💔 Breaking Change

  • Send PrivateLink config under privateService in create_inference_endpoint by @​co42 in #​4966
    • AWS PrivateLink settings are now sent as privateService.accountId and privateService.region. Use the new private_link_account_id and private_link_region parameters (the region is required when the account ID is set, and is independent of the compute region). The legacy account_id keyword still exists but is ignored and emits a FutureWarning; it is no longer included as a top-level payload field.

🖥️ CLI

  • [CLI] Honor --format / --json / -q on jobs run commands by @​Wauplin in #​4936 — docs
    • These flags previously leaked into the container command on hf jobs run, hf jobs uv run and their scheduled variants (--format became the script path, -q became the image name). They are now consumed wherever they appear; use -- when your script needs them.
  • [CLI] Allow bucket as a watched item type in hf webhooks create --watch by @​davanstrien in #​4958 — docs

📖 Documentation

🐛 Bug and typo fixes

🏗️ Internal

v1.32.0: [v1.32.0] Shared blob store, sandbox security hardening and faster imports

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📂 [Cache] Shared blob store: deduplicate Xet files across repos

The cache now deduplicates Xet files across repos. A Xet file downloaded through hf_xet is stored once at <CACHE_DIR>/blobs/<prefix>/<xet_hash> and every repo that needs it gets a relative symlink instead of a download: no bytes are transferred and no extra space is used, even across different repos — or after the repo that first downloaded the file was deleted. The per-repo snapshot layout is unchanged, older clients keep reading and downloading normally, and any failure to share silently falls back to regular repo-local storage. Set HF_HUB_DISABLE_SHARED_BLOBS=1 to opt out entirely. Shared files carry a <xet_hash>.refs manifest listing the repo blobs referencing them, which hf cache rm consults on deletion and hf cache prune sweeps to reclaim payloads that no cached repo uses anymore.

📚 Documentation: Manage your cache

💻 [Jobs] Ship config inside UV scripts

A UV script that only runs correctly on a specific runtime can now carry that runtime with it. An optional [tool.hf-jobs] table in the script's PEP 723 header accepts image, flavor, python, timeout, name, namespace, env, secrets, labels, volumes, network_group and network_aliases, and hf jobs uv run reads it at submit time. CLI flags

[!IMPORTANT]
✂ PR body was truncated to here.

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@renovate renovate Bot added lifecycle Update or deprecate something renovate labels Oct 5, 2026
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renovate Bot requested a review from freinold October 5, 2026 01:02
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⚠️ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

♻ Renovate will retry this branch, including artifacts, only when one of the following happens:

  • any of the package files in this branch needs updating, or
  • the branch becomes conflicted, or
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The artifact failure details are included below:

File name: uv.lock
Using CPython 3.14.7 interpreter at: /opt/containerbase/tools/python/3.14.7/bin/python3.14
error: No solution found when resolving dependencies for split (markers: python_full_version == '3.14.7' and sys_platform == 'win32')
  cause: Because gradio==6.25.0 depends on huggingface-hub>=1.16.0,<2.0 and your project depends on gradio==6.25.0, we can conclude that your project depends on huggingface-hub>=1.16.0,<2.0.
         And because your project depends on huggingface-hub==2.3.0, we can conclude that your project's requirements are unsatisfiable.

hint: The resolution failed for an environment that is not the current one, consider limiting the environments with `tool.uv.environments`.

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@renovate
renovate Bot force-pushed the renovate/huggingface-hub-2.x branch from 3a758d4 to 2af6ed2 Compare October 8, 2026 16:06
@renovate
renovate Bot force-pushed the renovate/huggingface-hub-2.x branch from 2af6ed2 to 60f6963 Compare October 23, 2026 10:44
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