--- title: "UER-py vs FineTuningLLMs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dbiir-uer-py-vs-dvgodoy-finetuningllms" tools: ["dbiir-uer-py", "dvgodoy-finetuningllms"] --- # UER-py vs FineTuningLLMs *GraphCanon updated Aug 24, 2026* ## Verdict Pick UER-py if uER-py, an open-source PyTorch framework with a diverse model zoo for training and fine-tuning language models; pick FineTuningLLMs if fineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. [UER-py](https://github.com/dbiir/UER-py/wiki) reports 3.1k GitHub stars, 520 forks, and 136 open issues, last pushed May 9, 2024. [FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) has 855 stars, 116 forks, and 4 open issues, last pushed Feb 28, 2026. Figures are from public GitHub metadata via [UER-py's repository](https://github.com/dbiir/UER-py) and [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs). | | [UER-py](/tools/dbiir-uer-py.md) | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | | --- | --- | --- | | Tagline | Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | | Stars | 3,112 | 855 | | Forks | 520 | 116 | | Open issues | 136 | 4 | | Language | Python | Jupyter Notebook | | Adopt for | UER-py, an open-source PyTorch framework with a diverse model zoo for training and fine-tuning language models. | FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [UER-py](/tools/dbiir-uer-py.md) | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 836d | 176d | | Open issues (now) | 136 | 4 | | Stars delta | +2 (30d) | +4 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/dbiir-uer-py/trust.md) | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | ## Decision facts: UER-py - **Pricing:** freemium - The framework itself is free and open-source under Apache 2.0 license providing flexibility for modification with no costs. - **Requirements:** Min 8 GB RAM; - Requires Python environment setup; - Needs PyTorch installation - **Adopt for:** UER-py, an open-source PyTorch framework with a diverse model zoo for training and fine-tuning language models. ## Decision facts: FineTuningLLMs - **Adopt for:** FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. ## Choose when ### Choose UER-py if… - UER-py is primarily Python; FineTuningLLMs is Jupyter Notebook. - License: UER-py is Apache-2.0, FineTuningLLMs is MIT. - Pricing: The framework itself is free and open-source under Apache 2.0 license providing flexibility for modification with no costs.. - Requirements: Min 8 GB RAM; - Requires Python environment setup; - Needs PyTorch installation. - Tags unique to UER-py: albert, bart, bert, chinese. - - When you need to work exclusively within the PyTorch ecosystem, UER-py provides extensive support for various pre-trained models and tasks without the necessity of switching frameworks. ### Choose FineTuningLLMs if… - FineTuningLLMs is primarily Jupyter Notebook; UER-py is Python. - License: FineTuningLLMs is MIT, UER-py is Apache-2.0. - Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, large language models. - You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem ## When NOT to use UER-py - - When you require more framework flexibility and are open to using TensorFlow or other deep learning libraries outside PyTorch. - - If your project is sensitive to maintenance updates but the UER-py repository has not seen recent active contribution, preferring a tool actively maintained might be better. ## When NOT to use FineTuningLLMs - Not interested in PyTorch; prefer TensorFlow or another framework - Seek theoretical background over practical applications ## Common questions ### What is the difference between UER-py and FineTuningLLMs? UER-py: Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo. FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. See the comparison table for live GitHub stats and shared categories. ### When should I choose UER-py over FineTuningLLMs? Choose UER-py over FineTuningLLMs when UER-py is primarily Python; FineTuningLLMs is Jupyter Notebook; License: UER-py is Apache-2.0, FineTuningLLMs is MIT; Pricing: The framework itself is free and open-source under Apache 2.0 license providing flexibility for modification with no costs.; Requirements: Min 8 GB RAM; - Requires Python environment setup; - Needs PyTorch installation; Tags unique to UER-py: albert, bart, bert, chinese; - When you need to work exclusively within the PyTorch ecosystem, UER-py provides extensive support for various pre-trained models and tasks without the necessity of switching frameworks. ### When should I choose FineTuningLLMs over UER-py? Choose FineTuningLLMs over UER-py when FineTuningLLMs is primarily Jupyter Notebook; UER-py is Python; License: FineTuningLLMs is MIT, UER-py is Apache-2.0; Tags unique to FineTuningLLMs: bitsandbytes, finetuning, hugging-face, large language models; You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem. ### When should I avoid UER-py? - When you require more framework flexibility and are open to using TensorFlow or other deep learning libraries outside PyTorch. - If your project is sensitive to maintenance updates but the UER-py repository has not seen recent active contribution, preferring a tool actively maintained might be better. ### When should I avoid FineTuningLLMs? Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications ### Is UER-py or FineTuningLLMs more popular on GitHub? UER-py has more GitHub stars (3,112 vs 855). Stars measure visibility, not whether either tool fits your constraints. ### Are UER-py and FineTuningLLMs open source? Yes - both are open-source projects on GitHub (UER-py: Apache-2.0, FineTuningLLMs: MIT). ### Where can I find alternatives to UER-py or FineTuningLLMs? GraphCanon lists graph-backed alternatives at [UER-py alternatives](/tools/dbiir-uer-py/alternatives) and [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) ([UER-py markdown twin](/tools/dbiir-uer-py/alternatives.md), [FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/dbiir-uer-py-vs-dvgodoy-finetuningllms.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, UER-py or FineTuningLLMs? UER-py: Dormant. FineTuningLLMs: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for UER-py and FineTuningLLMs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [UER-py trust report](/tools/dbiir-uer-py/trust); [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dbiir-uer-py`](/api/graphcanon/graph?tool=dbiir-uer-py) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_