Merge pull request #3560 from AI-Hypercomputer:fix_markdown

PiperOrigin-RevId: 893813217

Author: Google-ML-Automation

docs/guides.md

@@ -18,45 +18,45 @@
 
 Explore our how-to guides for optimizing, debugging, and managing your MaxText workloads.
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} ⚡ Optimization
+:::{grid-item-card} ⚡ Optimization
 :link: guides/optimization
 :link-type: doc
 
 Techniques for maximizing performance, including sharding strategies, Pallas kernels, and benchmarking.
 :::
 
-:::\{grid-item-card} 💾 Data Pipelines
+:::{grid-item-card} 💾 Data Pipelines
 :link: guides/data_input_pipeline
 :link-type: doc
 
 Configure input pipelines using **Grain** (recommended for determinism), **HuggingFace**, or **TFDS**.
 :::
 
-:::\{grid-item-card} 🔄 Checkpointing
+:::{grid-item-card} 🔄 Checkpointing
 :link: guides/checkpointing_solutions
 :link-type: doc
 
 Manage GCS checkpoints, handle preemption with emergency checkpointing, and configure multi-tier storage.
 :::
 
-:::\{grid-item-card} 🔍 Monitoring & Debugging
+:::{grid-item-card} 🔍 Monitoring & Debugging
 :link: guides/monitoring_and_debugging
 :link-type: doc
 
 Tools for observability: goodput monitoring, hung job debugging, and Vertex AI TensorBoard integration.
 :::
 
-:::\{grid-item-card} 🐍 Python Notebooks
+:::{grid-item-card} 🐍 Python Notebooks
 :link: guides/run_python_notebook
 :link-type: doc
 
 Interactive development guides for running MaxText on Google Colab or local JupyterLab environments.
 :::
 
-:::\{grid-item-card} 🌱 Model Bringup
+:::{grid-item-card} 🌱 Model Bringup
 :link: guides/model_bringup
 :link-type: doc
 

docs/guides/checkpointing_solutions.md

@@ -2,31 +2,31 @@
 
 # Checkpointing
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 💾 GCS Checkpointing
+:::{grid-item-card} 💾 GCS Checkpointing
 :link: checkpointing_solutions/gcs_checkpointing
 :link-type: doc
 
 Standard checkpointing to Google Cloud Storage.
 :::
 
-:::\{grid-item-card} 🚑 Emergency Checkpointing
+:::{grid-item-card} 🚑 Emergency Checkpointing
 :link: checkpointing_solutions/emergency_checkpointing
 :link-type: doc
 
 Handle preemption and recover training progress.
 :::
 
-:::\{grid-item-card} 🗄️ Multi-tier checkpointing
+:::{grid-item-card} 🗄️ Multi-tier checkpointing
 :link: checkpointing_solutions/multi_tier_checkpointing
 :link-type: doc
 
 Optimize storage costs and performance with multi-tier usage.
 :::
 
-:::\{grid-item-card} 🔁 Checkpoint conversion utilities
+:::{grid-item-card} 🔁 Checkpoint conversion utilities
 :link: checkpointing_solutions/convert_checkpoint
 :link-type: doc
 

docs/guides/monitoring_and_debugging.md

@@ -16,52 +16,52 @@
 
 # Monitoring and debugging
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 🕵️ Features & Diagnostics
+:::{grid-item-card} 🕵️ Features & Diagnostics
 :link: monitoring_and_debugging/features_and_diagnostics
 :link-type: doc
 
 Diagnostic tools and features for monitoring MaxText.
 :::
 
-:::\{grid-item-card} ☁️ GCP Observability
+:::{grid-item-card} ☁️ GCP Observability
 :link: monitoring_and_debugging/gcp_workload_observability
 :link-type: doc
 
 Observability for workloads running on Google Cloud Platform.
 :::
 
-:::\{grid-item-card} 🚫 Hang Playbook
+:::{grid-item-card} 🚫 Hang Playbook
 :link: monitoring_and_debugging/megascale_hang_playbook
 :link-type: doc
 
 Troubleshooting guide for training hangs at megascale.
 :::
 
-:::\{grid-item-card} 📈 Goodput
+:::{grid-item-card} 📈 Goodput
 :link: monitoring_and_debugging/monitor_goodput
 :link-type: doc
 
 Monitoring efficient training time (Goodput).
 :::
 
-:::\{grid-item-card} 📊 Logs & Metrics
+:::{grid-item-card} 📊 Logs & Metrics
 :link: monitoring_and_debugging/understand_logs_and_metrics
 :link-type: doc
 
 Understanding MaxText logs and performance metrics.
 :::
 
-:::\{grid-item-card} 📉 TensorBoard
+:::{grid-item-card} 📉 TensorBoard
 :link: monitoring_and_debugging/use_vertex_ai_tensorboard
 :link-type: doc
 
 Using Vertex AI TensorBoard for visualization.
 :::
 
-:::\{grid-item-card} ⏱️ XProf
+:::{grid-item-card} ⏱️ XProf
 :link: monitoring_and_debugging/xprof_user_guide
 :link-type: doc
 

docs/guides/optimization.md

@@ -18,31 +18,31 @@
 
 Explore techniques for maximizing performance, including model customization, sharding strategies, Pallas kernels, and benchmarking.
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 🛠️ Customizing Model Configs
+:::{grid-item-card} 🛠️ Customizing Model Configs
 :link: optimization/custom_model
 :link-type: doc
 
 Optimize and customize your LLM model configurations for higher performance (MFU) on TPUs.
 :::
 
-:::\{grid-item-card} 🥞 Sharding Strategies
+:::{grid-item-card} 🥞 Sharding Strategies
 :link: optimization/sharding
 :link-type: doc
 
 Choose efficient sharding strategies (FSDP, TP, EP, PP) using Roofline Analysis and understand arithmetic intensity.
 :::
 
-:::\{grid-item-card} ⚡ Pallas Kernels
+:::{grid-item-card} ⚡ Pallas Kernels
 :link: optimization/pallas_kernels_performance
 :link-type: doc
 
 Optimize with Pallas kernels for fine-grained control.
 :::
 
-:::\{grid-item-card} 📈 Benchmarking & Tuning
+:::{grid-item-card} 📈 Benchmarking & Tuning
 :link: optimization/benchmark_and_performance
 :link-type: doc
 

docs/reference.md

@@ -18,31 +18,31 @@
 
 Deep dive into MaxText architecture, models, and core concepts.
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 📊 Performance Metrics
+:::{grid-item-card} 📊 Performance Metrics
 :link: reference/performance_metrics
 :link-type: doc
 
 Understanding Model Flops Utilization (MFU), calculation methods, and why it matters for performance optimization.
 :::
 
-:::\{grid-item-card} 🤖 Models
+:::{grid-item-card} 🤖 Models
 :link: reference/models
 :link-type: doc
 
 Supported models and architectures, including Llama, Qwen, and Mixtral. Details on tiering and new additions.
 :::
 
-:::\{grid-item-card} 🏗️ Architecture
+:::{grid-item-card} 🏗️ Architecture
 :link: reference/architecture
 :link-type: doc
 
 High-level overview of MaxText design, JAX/XLA choices, and how components interact.
 :::
 
-:::\{grid-item-card} 💡 Core Concepts
+:::{grid-item-card} 💡 Core Concepts
 :link: reference/core_concepts
 :link-type: doc
 

docs/reference/architecture.md

@@ -1,16 +1,16 @@
 # Architecture
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 🗺️ Overview
+:::{grid-item-card} 🗺️ Overview
 :link: architecture/architecture_overview
 :link-type: doc
 
 High-level overview of MaxText design and components.
 :::
 
-:::\{grid-item-card} 📚 JAX/AI Libraries
+:::{grid-item-card} 📚 JAX/AI Libraries
 :link: architecture/jax_ai_libraries_chosen
 :link-type: doc
 

docs/reference/core_concepts.md

@@ -16,45 +16,45 @@
 
 # Core concepts
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 💾 Checkpoints
+:::{grid-item-card} 💾 Checkpoints
 :link: core_concepts/checkpoints
 :link-type: doc
 
 Understanding checkpoint formats and strategies.
 :::
 
-:::\{grid-item-card} ⚖️ Alternatives
+:::{grid-item-card} ⚖️ Alternatives
 :link: core_concepts/alternatives
 :link-type: doc
 
 Comparison with other frameworks like Megatron-LM.
 :::
 
-:::\{grid-item-card} 📉 Quantization
+:::{grid-item-card} 📉 Quantization
 :link: core_concepts/quantization
 :link-type: doc
 
 Techniques for reducing model size and improving performance.
 :::
 
-:::\{grid-item-card} 🧱 Tiling
+:::{grid-item-card} 🧱 Tiling
 :link: core_concepts/tiling
 :link-type: doc
 
 Understanding tiling strategies for partitioning logic.
 :::
 
-:::\{grid-item-card} ⚡ JAX/XLA/Pallas
+:::{grid-item-card} ⚡ JAX/XLA/Pallas
 :link: core_concepts/jax_xla_and_pallas
 :link-type: doc
 
 How MaxText leverages JAX, XLA, and Pallas for efficiency.
 :::
 
-:::\{grid-item-card} 🧠 MoE Configuration
+:::{grid-item-card} 🧠 MoE Configuration
 :link: core_concepts/moe_configuration
 :link-type: doc
 

docs/reference/models.md

@@ -1,16 +1,16 @@
 # Models
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 🥇 Tiering
+:::{grid-item-card} 🥇 Tiering
 :link: models/tiering
 :link-type: doc
 
 Optimized model tiers (Gold, Silver) for various TPU generations.
 :::
 
-:::\{grid-item-card} 🏗️ Supported Models
+:::{grid-item-card} 🏗️ Supported Models
 :link: models/supported_models_and_architectures
 :link-type: doc
 

docs/run_maxtext.md

@@ -2,38 +2,38 @@
 
 Choose your environment and orchestration method to run MaxText.
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 💻 Localhost / Single VM
+:::{grid-item-card} 💻 Localhost / Single VM
 :link: run_maxtext/run_maxtext_localhost
 :link-type: doc
 
 Get started quickly on a single machine. Clone the repo, install dependencies, and run your first training job on a single TPU or GPU VM.
 :::
 
-:::\{grid-item-card} 🎮 Single-host GPU
+:::{grid-item-card} 🎮 Single-host GPU
 :link: run_maxtext/run_maxtext_single_host_gpu
 :link-type: doc
 
 Run MaxText on single-host NVIDIA GPUs (e.g., A3 High/Mega). Includes Docker setup, NVIDIA Container Toolkit installation, and 1B/7B model training examples.
 :::
 
-:::\{grid-item-card} 🏗️ At scale with XPK (GKE)
+:::{grid-item-card} 🏗️ At scale with XPK (GKE)
 :link: run_maxtext/run_maxtext_via_xpk
 :link-type: doc
 
 Deploy to Google Kubernetes Engine (GKE) using XPK. Orchestrate large-scale training jobs on TPU or GPU clusters with simple CLI commands.
 :::
 
-:::\{grid-item-card} 🌐 Multi-host via Pathways
+:::{grid-item-card} 🌐 Multi-host via Pathways
 :link: run_maxtext/run_maxtext_via_pathways
 :link-type: doc
 
 Run large-scale JAX jobs on TPUs using Pathways. Supports batch and headless (interactive) workloads on GKE.
 :::
 
-:::\{grid-item-card} 🔌 Decoupled Mode
+:::{grid-item-card} 🔌 Decoupled Mode
 :link: run_maxtext/decoupled_mode
 :link-type: doc
 

docs/tutorials.md

@@ -18,31 +18,31 @@
 
 Explore our tutorials to learn how to use MaxText, from your first run to advanced post-training techniques.
 
-::::\{grid} 1 2 2 2
+::::{grid} 1 2 2 2
 :gutter: 2
 
-:::\{grid-item-card} 🚀 Getting Started
+:::{grid-item-card} 🚀 Getting Started
 :link: tutorials/first_run
 :link-type: doc
 
 Installation, prerequisites, verification, and your first training run.
 :::
 
-:::\{grid-item-card} 📚 Pre-training
+:::{grid-item-card} 📚 Pre-training
 :link: tutorials/pretraining
 :link-type: doc
 
 Step-by-step guides for pre-training with real datasets like C4 using HuggingFace, Grain, or TFDS.
 :::
 
-:::\{grid-item-card} 🧩 Post-training
+:::{grid-item-card} 🧩 Post-training
 :link: tutorials/post_training_index
 :link-type: doc
 
 Techniques for SFT, RL, and other post-training workflows on TPU.
 :::
 
-:::\{grid-item-card} 📊 Inference
+:::{grid-item-card} 📊 Inference
 :link: tutorials/inference
 :link-type: doc