Fine-tuning
Train and host custom models on your own data.
33 tools
Fine-tuning has gone from "deep ML team only" to "a few hours of JSONL away" — but the choice between closed-model FT (OpenAI), open-model FT (Together, Modal), and memory-tuning matters more than ever.
Covers closed-model fine-tuning (OpenAI), open-model FT + serving (Together AI, Replicate, Modal), distributed training platforms (Anyscale), and specialised platforms (Lamini for factual recall).
Pick OpenAI for the easiest UX on closed models. Pick Together AI for open-model FT + serving in one place. Pick Modal for serverless GPU control. Pick Lamini specifically for hallucination-free factual recall.
Together AI
FeaturedFine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
Modal
Serverless GPUs and infra for training & serving ML.
Replicate
One-API platform for running and fine-tuning open-source models.
OpenAI Fine-tuning
Fine-tune GPT-4o-mini and friends on your own data.
Llama
Meta's open-weight LLM family covering 1B mobile models up to 405B frontier and natively multimodal 10M-context Llama 4 variants.
RunPod
On-demand GPU cloud and serverless inference platform built specifically for AI workloads.
vLLM
Open-source high-throughput inference engine for serving LLMs with PagedAttention and continuous batching.
CoreWeave
AI-native GPU cloud built for large-scale training, fine-tuning, and inference on NVIDIA hardware.
Ludwig
Declarative, YAML-driven deep learning framework for fine-tuning LLMs and multi-modal models without writing training loops.
OpenPipe
Fine-tuning and reinforcement learning platform for turning expensive prompts into cheap, fast, task-specific models.
SGLang
Open-source high-throughput inference engine for LLMs and multimodal models with OpenAI-compatible serving.
Unsloth
Open-source LLM fine-tuning toolkit with custom kernels that train 2-30x faster and use up to 90% less VRAM.
Hugging Face AutoTrain
No-code fine-tuning and training pipeline that spins up state-of-the-art models on the Hugging Face Hub.
Lambda
On-demand NVIDIA GPU cloud built specifically for training, fine-tuning, and serving large AI models.
Optuna
Open-source Python framework for automated hyperparameter optimization across any ML stack.
Ray Tune
Open-source Python library for distributed hyperparameter tuning at any scale.
Together AI Fine-tuning
Managed fine-tuning platform for open-source LLMs and vision models with LoRA, full fine-tuning, and RL support.
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Edge Impulse
End-to-end platform for training and deploying ML models on microcontrollers, sensors, and other edge hardware.
Anyscale
Ray-powered platform for training, serving, and scaling LLMs.
Fireworks AI
Production inference and fine-tuning platform for open-source LLMs, tuned for speed and enterprise economics.
Lamini
Memory-tuning platform for grounding LLMs in your facts.
FedML
Distributed training, fine-tuning, and serving platform with federated learning roots.
Pachyderm
Kubernetes-native data versioning and pipeline engine for reproducible ML at petabyte scale.
LLaMA Factory
Open-source, no-code WebUI for fine-tuning 100+ open LLMs with LoRA, QLoRA, DPO, and PPO.