huggingface

library0.0.1pypypiunverified

The `huggingface` PyPI package (version 0.0.1) is a meta-package designed to simplify installation by pulling in the main Hugging Face libraries: `transformers`, `datasets`, and `huggingface_hub`. It does not provide its own direct API functionality. This package typically has a very low release cadence, primarily updating its dependencies.

ai-ml llm-agents

pip install huggingface

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · HUGGINGFACE

huggingface

ai-mlpythonv0.0.1

Install

1.5s avg

Import

—

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.0.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 17.8MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 1.5s · import 0.000s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

pipeline

✓ from transformers import pipeline

✗ from transformers import pipeline

The `huggingface` package itself does not expose an API. This quickstart demonstrates common usage of the `transformers` library (specifically the `pipeline` abstraction), which is automatically installed as a dependency by `huggingface`. All direct functionality will come from `transformers`, `datasets`, or `huggingface_hub`.

from transformers import pipeline # The huggingface meta-package itself does not provide an API. # This quickstart demonstrates typical usage of the `transformers` library, # which is installed as a dependency by `huggingface`. classifier = pipeline("sentiment-analysis") result = classifier("I love using Hugging Face libraries!") print(result) # Example of using a dataset (also installed by huggingface meta-package) from datasets import load_dataset # dataset = load_dataset("imdb") # Uncomment to load a large dataset # print(dataset)

Debug

Known issues

gotchaThe `huggingface` PyPI package is a meta-package (version 0.0.1) and does not provide direct API functionality. It primarily serves to install other core Hugging Face libraries (`transformers`, `datasets`, `huggingface_hub`).

fix

Always import classes and functions directly from `transformers`, `datasets`, or `huggingface_hub`, not `huggingface`.

affects: 0.0.1

gotchaAttempting to import or use functionality directly from `huggingface` (e.g., `from huggingface import pipeline`) will result in an `AttributeError` or `ModuleNotFoundError`.

fix

Identify which specific Hugging Face library provides the desired functionality (e.g., `transformers` for `pipeline`, `datasets` for `Dataset`) and import from that package.

affects: 0.0.1

Upgrade

Version history

0.0.1latest on PyPI · released Dec 18, 2020

Audit

Dependencies

transformersrequiredProvides state-of-the-art machine learning models for NLP, computer vision, and audio.

datasetsrequiredOffers an efficient way to access and share datasets for machine learning.

huggingface_hubrequiredClient library for interacting with the Hugging Face Hub (model/dataset storage and sharing).

Agent activity

24 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/huggingface/huggingface ↗

packagehttps://pypi.org/project/huggingface/ ↗

homepagehttps://huggingface.co ↗