> For the complete documentation index, see [llms.txt](https://docs.yottalabs.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.yottalabs.ai/tutorials.md).

# Tutorials

- [Platform Setup](https://docs.yottalabs.ai/tutorials/platform-setup.md)
- [How to Build Custom Images](https://docs.yottalabs.ai/tutorials/platform-setup/how-to-build-custom-images.md)
- [Training & Fine-tuning](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning.md)
- [Get Started in LLM Training with Pytorch 2.8.0](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/get-started-in-llm-training-with-pytorch-2.8.0.md)
- [Accelerating PyTorch Training with TorchDynamo and JIT](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/accelerating-pytorch-training-with-torchdynamo-and-jit.md)
- [Fine-tuning Orpheus\_(3B)-TTS with Unsloth](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/fine-tuning-orpheus_-3b-tts-with-unsloth.md)
- [GRPO on GSM8K with SkyRL](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/grpo-on-gsm8k-with-virtual-machine.md)
- [GRPO on MathVista with Unsloth](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/grpo-on-mathvista-with-unsloth.md)
- [Fine-tune a Reasoning Model to Think in Target Language with Unsloth](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/fine-tune-a-reasoning-model-to-think-in-target-language-with-unsloth.md)
- [SkyRL for LLM-as-a-Judge Training](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/skyrl-for-llm-as-a-judge-training.md)
- [Reinforced Learning with Miles](https://docs.yottalabs.ai/tutorials/training-and-fine-tuning/reinforced-learning-with-miles.md)
- [Inference & Serving](https://docs.yottalabs.ai/tutorials/inference-and-serving.md)
- [Guide to Serverless](https://docs.yottalabs.ai/tutorials/inference-and-serving/guide-to-serverless.md)
- [Queue-based Serverless Quickstart](https://docs.yottalabs.ai/tutorials/inference-and-serving/queue-based-serverless-quickstart.md)
- [LLM Serving on Yotta Labs with AWS Trainium](https://docs.yottalabs.ai/tutorials/inference-and-serving/llm-serving-on-yotta-labs-with-aws-trainium.md)
- [Running DFlash with Qwen3.6-35B-A3B on RTX PRO 6000](https://docs.yottalabs.ai/tutorials/inference-and-serving/running-dflash-with-qwen3.6-35b-a3b-on-rtx-pro-6000.md)
- [Run DeepSeek V4 Flash/Pro on B300](https://docs.yottalabs.ai/tutorials/inference-and-serving/run-deepseek-v4-flash-pro-on-b300.md)
- [Image & Video Generation](https://docs.yottalabs.ai/tutorials/image-and-video-generation.md)
- [Generating Images with Z-Image Model Quickstart](https://docs.yottalabs.ai/tutorials/image-and-video-generation/generating-images-with-z-image-model-quickstart.md)
- [Generate Product Images with Wan2.1/2.2](https://docs.yottalabs.ai/tutorials/image-and-video-generation/generate-product-images-with-wan2.1-2.2.md)
- [Image Generation with FLUX.1-dev](https://docs.yottalabs.ai/tutorials/image-and-video-generation/image-generation-with-flux.1-dev.md)
- [Video Generation with ComfyUI](https://docs.yottalabs.ai/tutorials/image-and-video-generation/video-generation-with-comfyui.md)
- [Video Generation with ComfyUI-nunchaku](https://docs.yottalabs.ai/tutorials/image-and-video-generation/video-generation-with-comfyui-nunchaku.md)
- [Quant-VideoGen on RTX 5090](https://docs.yottalabs.ai/tutorials/image-and-video-generation/quant-videogen-on-rtx-5090.md)
- [Sparse-VideoGen on NVIDIA H200](https://docs.yottalabs.ai/tutorials/image-and-video-generation/sparse-videogen-on-nvidia-h200.md)
- [3DGRUT on A100: Build your own 3D Scene Reconstruction](https://docs.yottalabs.ai/tutorials/image-and-video-generation/3dgrut-on-a100-build-your-own-3d-scene-reconstruction.md)
- [Sol-RL on A100: Post-Training Diffusion Models at the Speed of Light](https://docs.yottalabs.ai/tutorials/image-and-video-generation/sol-rl-on-a100-post-training-diffusion-models-at-the-speed-of-light.md)
- [SANA-WM: Deploying NVIDIA's World Model on a Single RTX Pro 6000](https://docs.yottalabs.ai/tutorials/image-and-video-generation/sana-wm-deploying-nvidias-world-model-on-a-single-rtx-pro-6000.md)
- [AI Agents](https://docs.yottalabs.ai/tutorials/ai-agents.md)
- [NemoClaw with Local Inference](https://docs.yottalabs.ai/tutorials/ai-agents/nemoclaw-with-local-inference.md)
- [Buiding Your Own Chatbot in Feishu with Openclaw-lite](https://docs.yottalabs.ai/tutorials/ai-agents/buiding-your-own-chatbot-in-feishu-with-openclaw-lite.md)
- [Start Your Local Openclaw Bot with 1 Click](https://docs.yottalabs.ai/tutorials/ai-agents/start-your-local-openclaw-bot-with-1-click.md)
- [SkyPilot](https://docs.yottalabs.ai/tutorials/skypilot.md)
- [Getting started with YottaLabs on SkyPilot](https://docs.yottalabs.ai/tutorials/skypilot/getting-started-with-yottalabs-on-skypilot.md): Run your first GPU job
- [Training a simple MNIST model on YottaLabs with SkyPilot](https://docs.yottalabs.ai/tutorials/skypilot/training-a-simple-mnist-model-on-yottalabs-with-skypilot.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.yottalabs.ai/tutorials.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
