Best AI tools for distillation
37 tools in the Fine-tuning category, filtered to distillation.
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.
Paperspace Gradient
End-to-end MLOps platform with GPU notebooks, training jobs, and model deployment, now folded into DigitalOcean.
H2O AutoML
Open-source automated machine learning that handles feature engineering, model selection, and stacked ensembling out of the box.
Scale GenAI Platform
Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.
W&B Sweeps
Hyperparameter optimization from Weights & Biases with Bayesian search and Hyperband early stopping.
Forefront
Fine-tune and serve open-source LLMs on your own data without managing GPUs.
ONNX
Open standard for representing and exchanging machine learning models across frameworks and runtimes.
Apache SINGA
Apache-licensed distributed deep learning library focused on scalable training across GPUs and nodes.
DagsHub
GitHub-style collaboration platform for ML datasets, experiments, and models with MLflow and DVC under the hood.
Velda
Serverless GPU orchestration that runs AI training and batch jobs without Docker or Kubernetes.
AutotuneLLM
An open-source optimization layer that sits between your app and Ollama to squeeze more performance out of local LLMs.
Colossal-AI
Making large AI models cheaper, faster, and more accessible through distributed training
Language Model Builder
Learn how LLMs work by building one on your Mac
PyTorch Lightning
The deep learning framework for professional AI researchers and ML engineers