OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
AI Models

Transformers

An open-source Python framework in the Hugging Face ecosystem that centralizes definitions for pretrained machine-learning models across text, computer vision, audio, video and multimodal tasks. It supports inference and training.

Independent OpenViST project profile, based on linked sources.

Transformers — OpenViST project profile in AI Models.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when a project needs a Python framework for inference or training across multiple model modalities and the required pretrained models are compatible with the framework.

Who it is for

  • Developers building applications with pretrained machine-learning models.
  • Teams working across text, vision, audio, video or multimodal workflows.
  • Engineers who need to run, train or fine-tune compatible models.

Documented uses

  • Run supported pretrained text models for inference.
  • Create computer-vision inference services.
  • Build audio or video processing workflows around compatible pretrained models.
  • Develop applications combining supported input modalities.
  • Train or fine-tune compatible pretrained models.
Before you choose

Requirements & limits

The repository is public and the project is licensed under Apache-2.0. It is identified as usable in cloud, self-hosted, server and desktop environments; deployment depends on the surrounding application.

  • Confirm that the specific model and task are supported.
  • Choose it when Python and the Hugging Face ecosystem fit the project.
  • Assess whether inference, training or fine-tuning is required.
  • Consider whether the application spans more than one supported modality.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

COMPARE OPTIONS

Compare options for Model inference and serving

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
TransformersRun supported pretrained text models for inference.Cloud, Desktop, Self-hosted, ServerThe repository is public and the project is licensed under Apache-2.0. It is identified as usable in cloud, self-hosted, server and desktop environments; deployment depends on the surrounding application.
Gemma3Moe BuilderConvert a dense Gemma-3-270m checkpoint into a model with a router and configurable expert count and top-k selection.CLI, Linux, macOS, Self-hostedThe repository documents local installation as a Python package and requires Python 3.10 or later. Training and routing tools require the optional `datasets` dependency.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
30 September 2026
Original website title
huggingface/transformers · Official homepage title · retained in its source language
How we review sourcesSuggest a correction