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@@ -1,19 +1,81 @@
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-# Trainium model cache
+# Trainium Model Cache
 
-TODO:
+The Trainium Model Cache is a remote cache for compiled Trainium models in the `neff` format. 
+It is integrated into the [`TrainiumTrainer`] class to enable loading pretrained models from the cache instead of compiling them locally. 
+This can speed up the training process by about –3x.
+
+The Trainium Model Cache is hosted on the [Hugging Face Hub](https://huggingface.co/aws-neuron/optimum-neuron-cache) and includes compiled files for all popular and supported pre-trained models `optimum-neuron`.
+
+When training a Transformers or Diffusion model with vanilla [`torch-neuronx`](https://github.com/aws-neuron/aws-neuron-samples/tree/master/torch-neuronx), the models needs to be first compiled. The compiled version is stored in a local directory, usually `/var/tmp/neuron-compile-cache`. 
+This means that every time you train a new model in a new environment, you need to recompile it, which takes a lot of time. 
+
+We created the Trainium Model Cache to solve this limitation by providing a public cache of precompiled available models and a private cache to create your private, secured, remote model cache.
+
+The Trainium Model Cache plugs into the local cache directory of the Hugging Face Hub. During training, the [`TrainiumTrainer`] will check if compilation files are available on the Hub and download them if they are found, allowing you to save both time and cost by skipping the compilation phase.
+
+## How the caching system works
+
+### Hash computation
+
+Many factors can trigger compilation among which: 
+
+- The model weights
+- The input shapes
+- The precision of the model, full-precision or bf16
+- The version of the Neuron X compiler
+- The number of Neuron cores used
+
+These parameters are used to compute a hash. This hash is then used to compare local hashes for our training session against hashes stored on the Hugging Face Hub, and act accordingly (download or push).
+
+### How to use the Trainium model cache
+
+The Public model cache will be used when your training script uses the [`TrainiumTrainer`]. There are no additional changes needed.
+
+### How to use a private Trainium model cache
+
+The repository for the public cache is `aws-neuron/optimum-neuron-cache`. This repository includes all precompiled files for commonly used models so that it is publicly available and free to use for everyone. But there are two limitations:
+
+1. You will not be able to push your own compiled files on this repo 
+2. It is public and you might want to use a private repo for private models
+
+To alleviate that [you can create your own private cache repository](https://huggingface.co/new) and set the environment variable `CUSTOM_CACHE_REPO`. For example, if you cache repo is called `michaelbenayoun/my_custom_cache_repo`, you just need to do:
+
+```bash
+CUSTOM_CACHE_REPO="michaelbenayoun/my_custom_cache_repo" torchrun ...
+```
+
+or:
+
+```bash
+export CUSTOM_CACHE_REPO="michaelbenayoun/my_custom_cache_repo"
+torchrun ...
+```
+
+You have to be [logged into the Hugging Face Hub](https://huggingface.co/docs/huggingface_hub/quick-start#login) to be able to push  and pull files from your private cache repository.
+
+### Cache system flow
+
+<p align="center">
+  <img alt="Cache system flow" src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/neuron/cache_system_flow.jpg">
+  <br>
+  <em style="color: grey">Cache system flow</em>
+</p>
+
+
+At each the beginning of each training step, the  [`TrainiumTrainer`] computes a `NeuronHash` and checks the cache repo(s) (official and custom) on the Hugging Face Hub to see if there are compiled files associated to this hash. 
+If that is the case, the files are downloaded directly to the local cache directory and no compilation is needed. Otherwise compilation is performed.
+
+
+Just as for downloading compiled files, the [`TrainiumTrainer`] will keep track of the newly created compilation files at each training step, and upload them to the Hugging Face Hub at save time or when training ends. This assumes that you have writing access to the cache repo, otherwise nothing will be pushed.