Fix broken links in README (nod-ai#527)

Co-authored-by: Daniel Garvey <34486624+dan-garvey@users.noreply.github.com>

README.md

@@ -10,8 +10,8 @@ is intended to be a general purpose model compilation and execution tool.
 Turbine provides three primary tools:
 
 * *AOT Export*: For compiling one or more `nn.Module`s to compiled, deployment
-  ready artifacts. This operates via both a [simple one-shot export API](https://github.com/nod-ai/SHARK-Turbine/blob/main/python/shark_turbine/aot/exporter.py)
-  for simple models and an underlying [advanced API](https://github.com/nod-ai/SHARK-Turbine/blob/main/python/shark_turbine/aot/compiled_module.py) for complicated models
+  ready artifacts. This operates via both a simple one-shot export API (Already upstreamed to [torch-mlir](https://github.com/llvm/torch-mlir/blob/main/python/torch_mlir/extras/fx_importer.py))
+  for simple models and an underlying [advanced API](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/shark_turbine/aot/compiled_module.py) for complicated models
   and accessing the full features of the runtime.
 * *Eager Execution*: A `torch.compile` backend is provided and a Turbine Tensor/Device
   is available for more native, interactive use within a PyTorch session.
@@ -62,11 +62,11 @@ compiler, these should be compilable via IREE with `--iree-input-type=torch` for
 end to end execution. Dynamic shape support in torch-mlir is a work in progress,
 and not everything works at head with release binaries at present.
 
-  * [AOT MLP With Static Shapes](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/aot_mlp/mlp_export_simple.py)
-  * [AOT MLP with a dynamic batch size](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/aot_mlp/mlp_export_dynamic.py)
+  * [AOT MLP With Static Shapes](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/aot_mlp/mlp_export_simple.py)
+  * [AOT MLP with a dynamic batch size](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/aot_mlp/mlp_export_dynamic.py)
   * [AOT llama2](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/llama2_inference/llama2.ipynb):
     Dynamic sequence length custom compiled module with state management internal to the model.
-  * [Eager MNIST with `torch.compile`](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/eager_mlp/mlp_eager_simple.py)
+  * [Eager MNIST with `torch.compile`](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/eager_mlp/mlp_eager_simple.py)
 
 ## Developers