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To streamline implementation,\nthe full suite of scorers is offered in this paper's "},{"type":"highlight","text":"companion"},{"type":"text","text":" Python toolkit,\nUQLM
from the top result below
https://huggingface.co/papers?q=companion
png","numComments":0,"upvoted":false,"isAuthorParticipating":false,"highlightedTitle":[{"type":"text","text":"The Binary Fraction of Red Supergiants in the Magellanic Clouds"}],"highlightedSummary":[{"type":"text","text":"Red supergiants (RSGs), as the descendants of OB-type stars and the\nprogenitors of supernovae
https://huggingface.co/datasets/microsoft/benchpress-score-matrix
00933 defines the full MCP-Atlas benchmark as 1,000 tasks over 36 real MCP servers and 220 tools; the ScaleAI/MCP-Atlas HF card and scaleapi/mcp-atlas GitHub repo expose the public release as 500 evaluation prompts/tasks, matching this MCPAtlas Public benchmark row
https://huggingface.co/docs/hub/storage-limits
If you are looking for more practical tips, check out this guide on how to upload large amount of data using the Python library
https://huggingface.co/papers?q=reflective%20essays
These techniques uncover useful student\nfeedback from thousands of comments, costing around 0
https://huggingface.co/datasets/teknium/OpenHermes-2.5
99934,"no_label_count":0,"no_label_proportion":0,"n_unique":175,"frequencies":{"International Liquidity Account":5,"Services Account":4,"Total Outlay/Expenditure Method":4,"Central Problems of an Economy":3,"Meaning of Deficient Demand":4,"Deficit and Surplus Balance of Payments":4,"Balance of Payments on Current
https://huggingface.co/docs/hub/models-inference
Inference Providers give developers streamlined, unified access to hundreds of machine learning models, powered by the best serverless inference partners
https://huggingface.co/docs/hub/storage-buckets-integrations
ls("buckets/username/my-bucket")
text_files = hffs
https://huggingface.co/blog/audio-datasets
Its minimalistic API allows users to download and prepare datasets in just one line of Python code, with a suite of functions that enable efficient pre-processing
https://huggingface.co/docs/hub/models-uploading
Models on the Hub are Git-based repositories, which give you versioning, branches, discoverability and sharing features, integration with dozens of libraries, and more
https://huggingface.co/docs/hub/agents-overview
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https://huggingface.co/docs/hub/storage-buckets-access
Copied
hf jobs run -v hf://buckets/username/my-bucket:/data python:3
https://huggingface.co/docs/hub/jobs-large-datasets
) works as-is (or just pick a bigger flavor — up to 1 TB of ephemeral disk)
https://huggingface.co/docs/hub/jobs-popular-images
A uv run --system-site-packages that would reuse the image’s packages and skip the reinstall is requested upstream
https://huggingface.co/docs/hub/jobs-overview
a UV or python command), a hardware flavor (CPU, GPU, TPU), and optionally a Docker image from Hugging Face Spaces or Docker Hub
https://huggingface.co/docs/hub/jobs-schedule
Use hf jobs uv run or hf jobs run with a schedule of @annually, @yearly, @monthly, @weekly, @daily, @hourly, or a CRON schedule expression (e
https://huggingface.co/docs/hub/agents-libraries
smolagents
smolagents is a lightweight Python library for building agents in a few lines of code
https://huggingface.co/docs/hub/jobs-reference
This client allows you to interact with the Hugging Face Hub directly in Python
https://huggingface.co/docs/hub/repositories-next-steps
How to programmatically manage repositories
Hugging Face supports accessing repos with Python via the huggingface_hub library
https://huggingface.co/docs/hub/spaces-storage
Buckets can be attached when creating a Space, from the Space settings UI, or programmatically via the huggingface_hub Python API
https://huggingface.co/docs/hub/spaces-changelog
2022-02-21 - Python versions
You can specify the version of Python that you want your Space to run on
https://huggingface.co/docs/hub/jobs-quickstart
Moreover, UV accepts the --with argument to define python dependencies, so we use --with trl to have the trl library available
https://huggingface.co/docs/hub/jobs-configuration
Alternatively, pass a Hugging Face token manually with --token in the CLI, or the token argument in Python
https://huggingface.co/docs/hub/jobs-manage
12-bookworm",
"space_id": null,
"command": ["bash", "-c", "python -c \"import urllib
https://huggingface.co/docs/hub/spaces-sdks-streamlit
Your code is rerun each time the state of the app changes
https://huggingface.co/docs/hub/spaces-oauth
CloudGoogle TPUsGradioHubHub Python LibraryHuggingface
https://huggingface.co/spaces/spacy/README/blob/main/README.md
The inference API currently supports NER out-of-the-box and you can try out your pipeline interactively in your browser
https://huggingface.co/docs/hub/webhooks
They allow you to listen for new changes on specific repos or to all repos belonging to particular set of users/organizations (not just your repos, but any repo)
https://huggingface.co/docs/hub/storage-buckets
Unlike Git-based repositories (models, datasets, Spaces), buckets are non-versioned and mutable, designed for use cases where you need simple, fast storage such as training checkpoints, logs, intermediate artifacts, or any large collection of files that doesn’t need version control
https://huggingface.co/docs/hub/spaces-dev-mode
CloudGoogle TPUsGradioHubHub Python LibraryHuggingface
https://huggingface.co/docs/hub/datasets-gated
A common use case of gated datasets is to provide access to early research datasets before the wider release