Transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Transformers is an open-source libraries and runtimes project on GitHub under the Apache-2.0 license (permissive), with 168k stars. It is built with CPython. Its last push was today.
- Stars
- 168k
- License
- Apache-2.0
- Activity
- Active
- Latest release
- v5.22.1
Judgement
- What it is
- Framework or platform
- What it does
- A library of model definitions and pretrained weights for text, vision, audio and multimodal models, for inference and training.
- Adopt it when
- You want to load, run or fine-tune open models from the Hugging Face Hub in Python.
- Watch out
- Fast-moving with frequent API changes, and not the fastest option for production serving.
- Ready for
- Production-ready
- Runs as
- Library
- Built with
- Python and PyTorch
- How established
- Established: started 8 years ago, latest release v5.22.1.
- What the license allows
- You can build it into a product you sell, as long as you keep its copyright notice.
Judged on 2026-11-03 from the project's README and GitHub data. The license and age lines are worked out directly.
Built from
Follow it down: Transformers → CPython → GCC → LLVM project → runs on a microchip
Built on Transformers: 9 projects
-
1
Manga Image Translator zyddnys
Translate manga/image 一键翻译各类图片内文字 https://cotrans.touhou.ai/ (no longer working)
Complete system Usable You want machine-translated manga pages and can run a GPU model locally.
★ 11k GPL-3.0 Python Active, pushed 22 days ago -
2
FastDeploy PaddlePaddle
High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle
Building block Usable You deploy ERNIE or other PaddlePaddle models, especially on Chinese hardware.
★ 3.7k Apache-2.0 Python Active, pushed 39 days ago -
3
OSWorld xlang-ai
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Developer tool Usable You research or build computer-use agents and need a standard way to measure them.
★ 3.2k Apache-2.0 Python Active, pushed today -
4
vLLM Ascend vllm-project
Community maintained hardware plugin for vLLM on Huawei Ascend
Integration Usable You have Huawei Ascend accelerators and want to use vLLM on them.
★ 3k Apache-2.0 Python Active, pushed today -
5
Mosec mosecorg
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
Framework or platform Usable You need to put custom PyTorch or TensorFlow models behind an efficient HTTP API with batching.
★ 903 Apache-2.0 Python Active, pushed today -
6
Parallax GradientHQ
Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere
Building block Experimental You want to experiment with running large models across several consumer machines.
★ 1.4k Apache-2.0 Python Slowing, pushed 4 months ago -
7
ZhiLight zhihu
A highly optimized LLM inference acceleration engine for Llama and its variants.
Building block Experimental You run Llama or DeepSeek models on PCIe consumer or data-centre GPUs and want to benchmark against vLLM.
★ 906 Apache-2.0 C++ Slowing, pushed 8 months ago -
8
Flama vortico
The production framework for Predictive and Generative AI. Serve any model as an API in one line, with OpenAI/Anthropic/Ollama-compatible endpoints, a built-in chat UI, and native MCP.
Framework or platform Usable You want one framework to expose scikit-learn, PyTorch or LLM models as production APIs with little code.
★ 304 Apache-2.0 Python Active, pushed today -
9
open-tutor-ai-CE Open-TutorAi
An open-source project designed to provide an educational and collaborative AI-powered platform
Complete system Experimental An education team wants to experiment with an AI tutor it can host.
★ 72 BSD-3-Clause JavaScript Slowing, pushed 4 months ago
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★ 89k MIT Go Active, pushed 24 days ago -
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Stars, license and activity come from GitHub and refresh on a rolling hourly schedule. The project's own description is quoted as written.