
LLaMA-Factory
Zero-code fine-tuning platform for diverse large language models
- Stars
- 66,240
- License
- Apache-2.0
- Last commit
- 1 day ago
Explore leading tools in the Model Training & Fine-Tuning Platforms category, including open-source options and SaaS products. Compare features, use cases, and find the best fit for your workflow.
10+ open-source projects · 6 SaaS products
These projects are active, self-hostable choices for knowledge management teams evaluating alternatives to SaaS tools.

Zero-code fine-tuning platform for diverse large language models

Accelerate LLM fine‑tuning with up to 2× speed and 70% less VRAM

Efficiently fine-tune large models with minimal parameters

Fine‑tune LLMs fast with flexible, scalable open‑source framework

End-to-end platform for building, training, and deploying foundation models

Rapid, lightweight fine-tuning for Stable Diffusion using LoRA
Zero-code fine-tuning platform for diverse large language models
Axolotl streamlines LLM and multimodal model fine‑tuning, offering LoRA, QLoRA, QAT, DPO, and multi‑GPU/Node support via simple YAML configs and Docker/PyPI deployment.
Understand the commercial incumbents teams migrate from and how many open-source alternatives exist for each product.
ML hub with curated foundation models, pretrained algorithms, and solution templates you can deploy and fine-tune in SageMaker
Ray-powered platform for scalable LLM training and inference.
Enterprise AI platform providing LLMs (Command, Aya) plus Embed/Rerank for retrieval
High-performance inference and fine-tuning platform for open and proprietary models.
API-first platform to run, fine-tune, and deploy AI models without managing infrastructure
AI acceleration cloud for fast inference, fine-tuning, and training via a simple API
Anyscale offers serverless endpoints and managed Ray clusters to serve, fine-tune, and evaluate models with autoscaling, GPUs, and enterprise controls.
Frequently replaced when teams want private deployments and lower TCO.
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