hamilton vs transformers
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| hamilton | transformers | |
|---|---|---|
| Tagline | Apache Hamilton helps define testable, modular, self-documenting dataflows. | 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models |
| Stars | 2.5k | 162k |
| Forks | 198 | 34k |
| Open issues | 153 | 2.5k |
| Language | Jupyter Notebook | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | Jul 3, 2026 | Jul 7, 2026 |
| Categories | Data & Retrieval, Model Training | Data & Retrieval, Model Training, LLM Frameworks |
hamilton
Apache Hamilton is a lightweight Python library for creating directed acyclic graphs (DAGs) of data transformations that run anywhere Python runs. It supports extensive features for defining and modifying DAG execution and is useful in various contexts including Airflow pipelines and FastAPI servers.
Jupyter Notebook
transformers
Repo hosts a Python library and framework for NLP, text, audio, vision, multimodal AI model creation, training and inference using PyTorch.
Python