ray-project--ray/doc/source/train/examples.yml

# This file is used to auto-generate the Examples Gallery page.
# Do not edit the generated examples.rst page directly.
# To request formatting changes to the generated page, file an issue with the Ray docs team.
# To reference the generated page, use examples.html.
# When adding a new example, include the skill level and framework, if applicable.

text: Below are examples for using Ray Train with a variety of frameworks and use cases. Ray Train makes it easy to scale out each of these examples to a large cluster of GPUs.
columns_to_show:
  - frameworks
groupby: skill_level
examples:
  - title: Distributing your PyTorch Training Code with Ray Train and Ray Data
    skill_level: beginner
    frameworks:
      - pytorch
    use_cases:
      - computer vision
    link: ../_collections/train/examples/pytorch/distributing-pytorch/README
  - title: Train an image classifier with Lightning
    skill_level: beginner
    frameworks:
      - lightning
    use_cases:
      - computer vision
    link: examples/lightning/lightning_mnist_example
  - title: Train a text classifier with Hugging Face Accelerate
    frameworks:
      - accelerate
      - pytorch
      - hugging face
    skill_level: beginner
    use_cases:
      - large language models
      - natural language processing
    link: examples/accelerate/accelerate_example
  - title: Train an image classifier with TensorFlow
    frameworks:
      - tensorflow
    skill_level: beginner
    use_cases:
      - computer vision
    link: examples/tf/tensorflow_mnist_example
  - title: Train a GPT-2-style Transformer with JAX and Flax
    frameworks:
      - jax
      - flax
    skill_level: beginner
    use_cases:
      - natural language processing
    link: examples/jax/intro_to_jax_trainer/README
  - title: Train with Horovod and PyTorch
    frameworks:
      - horovod
    skill_level: beginner
    link: examples/horovod/horovod_example
  - title: "Train ResNet model with Intel Gaudi"
    frameworks:
      - pytorch
    skill_level: beginner
    use_cases:
      - computer vision
    contributor: community
    link: examples/intel_gaudi/resnet
  - title: "Train BERT model with Intel Gaudi"
    frameworks:
      - transformers
    skill_level: beginner
    use_cases:
      - natural language processing
    contributor: community
    link: examples/intel_gaudi/bert
  - title: Profiling a Ray Train Workload with PyTorch Profiler
    frameworks:
      - pytorch
    skill_level: beginner
    use_cases:
      - computer vision
    link: ../_collections/train/examples/pytorch/pytorch-profiling/README
  - title: Get started with PyTorch Fully Sharded Data Parallel (FSDP2) and Ray Train
    skill_level: intermediate
    frameworks:
      - pytorch
    use_cases:
      - computer vision
    link: ../_collections/train/examples/pytorch/pytorch-fsdp/README
  - title: Get started with Tensor Parallelism (DeepSpeed AutoTP) and Ray Train
    skill_level: intermediate
    frameworks:
      - pytorch
      - deepspeed
    use_cases:
      - large language models
      - natural language processing
    link: ../_collections/train/examples/pytorch/tensor_parallel_autotp/README
  - title: Get started with 2D Parallelism (Tensor + Data Parallelism) using FSDP2 and Ray Train
    skill_level: intermediate
    frameworks:
      - pytorch
    use_cases:
      - large language models
      - natural language processing
    link: ../_collections/train/examples/pytorch/tensor_parallel_dtensor/README
  - title: Fine-tune an LLM with Ray Train and DeepSpeed
    skill_level: intermediate
    frameworks:
      - pytorch
      - deepspeed
    use_cases:
      - large language models
      - natural language processing
    link: ../_collections/train/examples/pytorch/deepspeed_finetune/README
  - title: Train a text classifier with DeepSpeed
    frameworks:
      - deepspeed
      - pytorch
    skill_level: intermediate
    use_cases:
      - large language models
      - natural language processing
    link: examples/deepspeed/deepspeed_example
  - title: Fine-tune a personalized Stable Diffusion model
    skill_level: intermediate
    frameworks:
      - pytorch
    use_cases:
      - computer vision
      - generative ai
    link: examples/pytorch/dreambooth_finetuning
  - title: Finetune Stable Diffusion and generate images with Intel Gaudi
    skill_level: intermediate
    frameworks:
      - accelerate
      - transformers
    use_cases:
      - computer vision
      - generative ai
    contributor: community
    link: examples/intel_gaudi/sd
  - title: Train a text classifier with PyTorch Lightning and Ray Data
    frameworks:
      - lightning
    skill_level: intermediate
    use_cases:
      - natural language processing
    link: examples/lightning/lightning_cola_advanced
  - title: Train a text classifier with Hugging Face Transformers
    frameworks:
      - transformers
    skill_level: intermediate
    use_cases:
      - natural language processing
    link: examples/transformers/huggingface_text_classification
  - title: RL Post-Train an LLM using HuggingFace TRL with GRPO
    frameworks:
      - transformers
      - trl
    skill_level: intermediate
    use_cases:
      - natural language processing
      - reinforcement learning
    link: examples/transformers/transformer_reinforcement_learning/README
  - title: "Fine-tune Llama-2-7b and Llama-2-70b with Intel Gaudi"
    frameworks:
      - accelerate
      - transformers
    skill_level: intermediate
    use_cases:
      - natural language processing
      - large language models
    contributor: community
    link: examples/intel_gaudi/llama
  - title: "Pre-train Llama-2 with Intel Gaudi"
    frameworks:
      - accelerate
      - transformers
      - deepspeed
    skill_level: intermediate
    use_cases:
      - natural language processing
      - large language models
    contributor: community
    link: examples/intel_gaudi/llama_pretrain

  - title: Fine-tune Llama3.1 with AWS Trainium
    frameworks:
      - pytorch
      - aws neuron
    skill_level: advanced
    use_cases:
      - natural language processing
      - large language models
    contributor: community
    link: examples/aws-trainium/llama3
  - title: Fine-tune a Llama-2 text generation model with DeepSpeed and Hugging Face Accelerate
    frameworks:
      - accelerate
      - deepspeed
      - hugging face
    skill_level: advanced
    use_cases:
      - natural language processing
      - large language models
    link: https://github.com/ray-project/ray/tree/master/doc/source/templates/04_finetuning_llms_with_deepspeed
  - title: Fine-tune a GPT-J-6B text generation model with DeepSpeed and Hugging Face Transformers
    frameworks:
      - hugging face
      - deepspeed
    skill_level: advanced
    use_cases:
      - natural language processing
      - large language models
      - generative ai
    link: examples/deepspeed/gptj_deepspeed_fine_tuning
  - title: Fine-tune a vicuna-13b text generation model with PyTorch Lightning and DeepSpeed
    frameworks:
      - lightning
      - deepspeed
    skill_level: advanced
    use_cases:
      - large language models
      - generative ai
    link: examples/lightning/vicuna_13b_lightning_deepspeed_finetune
  - title: Fine-tune a dolly-v2-7b text generation model with PyTorch Lightning and FSDP
    frameworks:
      - lightning
    skill_level: advanced
    use_cases:
      - large language models
      - generative ai
      - natural language processing
    link: examples/lightning/dolly_lightning_fsdp_finetuning
  - title: Train a tabular model with XGBoost
    frameworks:
      - xgboost
    skill_level: beginner
    link: ../_collections/ray-overview/examples/e2e-xgboost/README