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[Doc] Link to doc in README #740

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Expand Up @@ -23,6 +23,11 @@ On the low-level end, torchrl comes with a set of highly re-usable functionals f

TorchRL aims at (1) a high modularity and (2) good runtime performance.

## Documentation

The TorchRL documentation can be found [here](https://pytorch.org/rl).
It contains tutorials and the API reference.

## TensorDict as a common data carrier for RL

TorchRL relies on [`TensorDict`](https://github.com/pytorch-labs/tensordict/),
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