chore: import upstream snapshot with attribution

doc/source/train/examples.yml

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+# 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