Remove tutorials index content

Author: melissawm

docs/tutorials.md

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 # Tutorials
 
-For your first time running MaxText, we provide specific [instructions](first-run).
-
-MaxText supports training and inference of various open models.
-
-Some extra helpful guides:
-* [Gemma](https://ai.google.dev/gemma): a family of open-weights Large Language Model (LLM) by [Google DeepMind](https://deepmind.google/), based on Gemini research and technology. You can run decode and finetuning using [these instructions](https://github.com/AI-Hypercomputer/maxtext/blob/main/end_to_end/tpu/gemma/Run_Gemma.md).
-* [Llama2](https://llama.meta.com/llama2/): a family of open-weights Large Language Model (LLM) by Meta. You can run decode and finetuning using [these instructions](https://github.com/AI-Hypercomputer/maxtext/blob/main/end_to_end/tpu/llama2/run_llama2.md).
-* [Mixtral](https://mistral.ai/news/mixtral-of-experts/): a family of open-weights sparse mixture-of-experts (MoE) model by Mistral AI. You can run decode and finetuning using [these instructions](https://github.com/AI-Hypercomputer/maxtext/blob/main/end_to_end/tpu/mixtral/Run_Mixtral.md)
-
-In addition to the getting started guides, there are always other MaxText capabilities that are being constantly being added! The full suite of end-to-end tests is in [end_to_end](https://github.com/AI-Hypercomputer/maxtext/blob/main/end_to_end). We run them with a nightly cadence. They can be a good source for understanding MaxText Alternatively you can see the continuous [unit tests](https://github.com/AI-Hypercomputer/maxtext/blob/main/.github/workflows/RunTests.yml) which are run almost continuously.
-
-## End-to-end example
-
-See the <a href="https://www.kaggle.com/code/shivajidutta/maxtext-on-kaggle" target="_blank">MaxText example Kaggle notebook</a>.
-
-## Other examples
-
-You can also find other examples in the [MaxText repository](https://github.com/AI-Hypercomputer/maxtext/tree/main/pedagogical_examples).
-
-
-
 ```{toctree}
 :maxdepth: 1