# Manage Jobs ## List Jobs Find your list of Jobs in the Jobs page or your organization Jobs page (user/organization page > settings > Jobs): It is also available in the Hugging Face CLI. Show the list of running Jobs with `hf jobs ps` and use `-a` to show all the Jobs: ```bash >>> hf jobs ps JOB ID IMAGE/SPACE COMMAND CREATED STATUS ------------ ---------------- ----------- ------------------- ------- 69402ea6c... ghcr.io/astra... uv run p... 2025-12-15 15:52:06 RUNNING >>> hf jobs ps -a JOB ID IMAGE/SPACE COMMAND CREATED STATUS ------------ ---------- --------------- ------------------- --------- 69402ea6c... ghcr.io... uv run pytho... 2025-12-15 15:52:06 RUNNING 693b06b8c... ghcr.io... uv run pytho... 2025-12-11 18:00:24 CANCELED 693b069fc... ghcr.io... uv run pytho... 2025-12-11 17:59:59 ERROR 693aef401... ghcr.io... uv run pytho... 2025-12-11 16:20:16 COMPLETED 693aee76c... ubuntu echo Hello f... 2025-12-11 16:16:54 COMPLETED 693ae8e3c... python:... python -c pr... 2025-12-11 15:53:07 COMPLETED ``` Specify your organization `namespace` to list Jobs under your organization: ```bash >>> hf jobs ps --namespace ``` ## Filter Jobs Click on a Job's label to filter Jobs by label: In the CLI, you can filter Jobs based on conditions provided, using the format key=value: Filter by labels: ```bash >>> hf jobs ps --filter label=fine-tuning --filter label=model=Qwen3-06B -a JOB ID IMAGE/SPACE COMMAND CREATED STATUS ------------ ------------ ---------------- ------------------- --------- 6978b1254... ghcr.io/a... uv run --with... 2026-01-27 12:35:49 COMPLETED 6978b11d4... ghcr.io/a... uv run --with... 2026-01-27 12:33:53 COMPLETED ``` Filter on any condition: ```bash >>> hf jobs ps --filter status=error -a JOB ID IMAGE/SPACE COMMAND CREATED STATUS ------------ ---------- ------------------ ------------------- ------ 693b069fc... ghcr.io... uv run python -... 2025-12-11 17:59:59 ERROR 693996dec... ghcr.io... bash -c python ... 2025-12-10 15:50:54 ERROR 69399695c... ghcr.io... uv run --with t... 2025-12-10 15:49:41 ERROR 693994bdc... ghcr.io... uv run --with t... 2025-12-10 15:41:49 ERROR 68d3c1af3... ghcr.io... uv run bash -c ... 2025-09-24 10:02:23 ERROR ``` Filtering supports negation `!=` and glob patterns (including `*` and `?`): ```bash # Show Jobs that are not completed >>> hf jobs ps -a --filter status!=completed # Show Jobs with a command that ends with "train.py" >>> hf jobs ps -a --filter "command=*train.py" # Show Jobs with a "fine-tuning" label >>> hf jobs ps -a --filter label=fine-tuning # Show Jobs that don't have the "prod" label and have a label that starts with "data-" >>> hf jobs ps -a --filter label!=prod --filter "label=data-*" # Show Jobs based on key=value labels >>> hf jobs ps -a --filter label=model=Qwen3-06B --filter label=dataset!=Capybara ``` ## Monitor resource usage Use `hf jobs stats` to get the usage statistics for CPU, memory, network and GPU (if any) of running Jobs: ```bash >>> hf jobs stats JOB ID CPU % NUM CPU MEM % MEM USAGE NET I/O GPU UTIL % GPU MEM % GPU MEM USAGE ------------------------ ----- ------- ----- ---------------- --------------- ---------- --------- --------------- 695e83c5d2f3efac77e8cf18 8% 12.0 7.18% 10.9GB / 152.5GB 0.0bps / 0.0bps 100% 31.92% 25.9GB / 81.2GB ``` Specify one or several Job ids to only show the statistics of certain Jobs: ```bash >>> hf jobs stats [job-ids]... ``` ## Inspect a Job You can see the status logs of a Job in the Job page: Alternatively using the CLI ```bash >>> hf jobs inspect 693994e21a39f67af5a41ad0 [ { "id": "693994e21a39f67af5a41ad0", "created_at": "2025-12-10 15:42:26.835000+00:00", "docker_image": "ghcr.io/astral-sh/uv:python3.12-bookworm", "space_id": null, "command": ["bash", "-c", "python -c \"import urllib.request; import os; from pathlib import Path; o = urllib.request.build_opener(); o.addheaders = [(\\\"Authorization\\\", \\\"Bearer \\\" + os.environ[\\\"UV_SCRIPT_HF_TOKEN\\\"])]; Path(\\\"/tmp/script.py\\\").write_bytes(o.open(os.environ[\\\"UV_SCRIPT_URL\\\"]).read())\" && uv run --with trl /tmp/script.py"], "arguments": [], "environment": {"UV_SCRIPT_URL": "https://huggingface.co/datasets/lhoestq/hf-cli-jobs-uv-run-scripts/resolve/728cc5682eb402d7ffe66a2f6f97645b34cb08dd/train.py"}, "secrets": ["HF_TOKEN", "UV_SCRIPT_HF_TOKEN"], "flavor": "a100-large", "status": {"stage": "COMPLETED", "message": null}, "owner": {"id": "5e9ecfc04957053f60648a3e", "name": "lhoestq", "type": "user"}, "endpoint": "https://huggingface.co", "url": "https://huggingface.co/jobs/lhoestq/693994e21a39f67af5a41ad0" } ] ``` and for the logs ```bash >>> hf jobs logs 693994e21a39f67af5a41ad0 Downloading nvidia-cuda-nvrtc-cu12 (84.0MiB) Downloading numpy (15.8MiB) Downloading nvidia-cuda-cupti-cu12 (9.8MiB) Downloading tokenizers (3.1MiB) Downloading nvidia-cusolver-cu12 (255.1MiB) Downloading nvidia-cufft-cu12 (184.2MiB) Downloading transformers (11.4MiB) Downloading setuptools (1.1MiB) ... ``` Specify your organization `namespace` to inspect a Job under your organization: ```bash hf jobs inspect --namespace hf jobs logs --namespace ``` ## Debug a Job If a Job has an error, you can see it in on the Job page Look at the status message and the logs on the Job page to see what went wrong. You may also look at the last lines of logs to see what happened before a Job failed. You can see that in the Job page, or using the CLI: ```bash >>> hf jobs logs 69405cf51a39f67af5a41f29 | tail -n 10 Downloaded nvidia-cudnn-cu12 Downloaded torch Installed 66 packages in 226ms Generating train split: 100%|██████████| 15806/15806 [00:00<00:00, 73330.17 examples/s] Generating test split: 100%|██████████| 200/200 [00:00<00:00, 45427.32 examples/s] Traceback (most recent call last): File "/tmp/script.py", line 7, in train_dataset=train_dataset, ^^^^^^^^^^^^^ NameError: name 'train_dataset' is not defined. Did you mean: 'load_dataset'? ``` Debug a Job locally using your local UV or Docker setup: * `hf jobs uv run ...` -> `uv run ...` * `hf jobs run ...` -> `docker run ...` The status message can say "Job timeout": it means the Job didn't finish in time before the timeout (the default is 30min) and therefore it was stopped. In this case you need to specify a higher timeout, using `--timeout` in the CLI, e.g. ```bash hf jobs uv run --timeout 3h ... ``` ## Cancel Jobs Use the "Cancel" button on the Job page to cancel a Job: or in the CLI: ```bash hf jobs cancel 693b06b8c67c9f186cfe239e ``` Specify your organization `namespace` to cancel a Job under your organization: ```bash hf jobs cancel --namespace ``` ## MacOS menu bar Find your list of Jobs in the MacOS [`hfjobs-menubar`](https://github.com/drbh/hfjobs-menubar) client: Get Jobs information, and monitor logs and resource usage statistics: