Releasesby Glyphhuggingface_hub [v1.31.0] Custom labels for Sandboxes, More resilient downloads and more
🏷️ Custom labels for Sandboxes Dedicated sandboxes now accept custom labels, attached to the underlying Job. This is useful for cost attribution, bookkeeping, or finding and reconnecting to the sandboxes created by a given controller run. Labels use the same -l / --label KEY=VALUE syntax as hf jobs run .
Also shipped Sep 10, 2026Hugging Face in September 2026 →
BigQuery conversational analytics adds ML.CORRELATION in preview
Conversational analytics can now use ML.CORRELATION to calculate statistical correlations between a target column and one or more metric columns in a table.
BigQuery ML.METRICS evaluates predictions without a stored model
The preview ML.METRICS function computes classification or regression evaluation metrics on any table or query with actual and predicted values, with no need to create or reference a stored model.
You can use the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data
You can use the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data. This feature is in Preview .
BigQuery Data Engineering Agent integrates with BigQuery Graph
The Data Engineering Agent now uses BigQuery Graph for extra context between source and destination schemas, improving schema mapping accuracy in data engineering pipelines. It is generally available.
Using dbt artifacts for Slim CI and defer to production in dbt Projects on Snowflake (General availability)
Slim CI, defer to production, failed-execution recovery, and concurrent execution are now generally available for dbt Projects on Snowflake. Reuse dbt artifacts from recent production executions to accelerate development, streamline CI/CD workflows, and recover from failed production runs without maintaining a separate artifact store.
External secret providers (Preview)
External secret providers are now in preview. If your organization already keeps API keys, database passwords, and similar values in AWS Secrets Manager, Azure Key Vault, or Google Cloud Secret Manager, Snowflake can read those values when a query needs them, so you don't have to maintain a second copy in a Snowflake secret .
More from Hugging Face HubEvery Hugging Face Hub release →
[v1.32.0] Shared blob store, sandbox security hardening and faster imports
📂 [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...
[v2.0.0] The httpx2 release
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 .
[v1.33.0] Better UX on large uploads and simpler skills installs
📤 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.
Preview LeRobot Episodes
LeRobot datasets now open with an episode preview on the dataset page. Every camera plays on one shared transport, so you can scrub through an episode and see each angle at the same moment. Dataset listings also show robot type, episode count, and a preview of the first episode.
Hugging Face is now on Google Cloud Marketplace
Organizations can now subscribe to Hugging Face with their Google Cloud account. Usage for Inference Providers, Inference Endpoints, Spaces, Jobs, storage, and Team or Enterprise seats will appear on their Google Cloud invoice.
Live resource usage on Jobs
The job page has a new Resources panel next to the logs. While your job runs, it shows live CPU, RAM, GPU and VRAM usage, updated every couple of seconds.
Hugging Face Hub 2.1.1
[CLI] Rename 'hf spaces zero-gpu-quota' to 'hf spaces zero-gpu quota'- #5055
[v2.1.0] Better Jobs tooling, ZeroGPU quota tracking, and revamped Model Catalog
📊 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.