hiyouga/LlamaFactory vs ray-project/ray
Compare hiyouga/LlamaFactory and ray-project/ray using the current verified snapshot: positioning, license, deployment, use cases, limitations, and original sources.
hiyouga/LlamaFactory
LlamaFactory is a unified framework for fine-tuning large language models and vision-language models through a zero-code CLI and Web UI. It supports a wide range of training algorithms, quantization methods, and inference backends.
- License
- Apache-2.0
- Deployment
- Refer to project documentation
- Use cases
- AI engineers, developers, and researchers who need a unified framework for zero-code model customization and deployment via CLI or Web UI. · Users who need to run parameter-efficient fine-tuning on limited hardware, such as 4-bit QLoRA for a 7B model on 6GB VRAM.
- Updated
- —
ray-project/ray
A unified framework for scaling Python and AI applications from a single laptop to a cluster. It provides distributed abstractions for tasks, actors, and objects, alongside libraries for data processing, training, tuning, reinforcement learning, and serving.
- License
- Apache-2.0
- Deployment
- Refer to project documentation
- Use cases
- AI engineers and developers who need to scale Python applications across a cluster.
- Updated
- 2026-07-17T07:57:18Z
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