Rename Colab notebooks to highlight frameworks used. (#15162)

Also adjusted descriptions.

skip-ci: pure rename / comment changes
diff --git a/docs/website/docs/guides/ml-frameworks/tensorflow.md b/docs/website/docs/guides/ml-frameworks/tensorflow.md
index 2e48720..1e8753f 100644
--- a/docs/website/docs/guides/ml-frameworks/tensorflow.md
+++ b/docs/website/docs/guides/ml-frameworks/tensorflow.md
@@ -146,10 +146,10 @@
 
 | Colab notebooks |  |
 | -- | -- |
-Training an MNIST digits classifier | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/mnist_training.ipynb)
-Edge detection module | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/edge_detection.ipynb)
-Pretrained ResNet50 inference | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/resnet.ipynb)
-TensorFlow Hub Import | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_hub_import.ipynb)
+Training an MNIST digits classifier | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_mnist_training.ipynb)
+Edge detection | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_edge_detection.ipynb)
+Pretrained ResNet50 inference | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_resnet.ipynb)
+TensorFlow Hub import | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_hub_import.ipynb)
 
 End-to-end execution tests can be found in IREE's
 [integrations/tensorflow/e2e/](https://github.com/openxla/iree/tree/main/integrations/tensorflow/e2e)
diff --git a/samples/colab/README.md b/samples/colab/README.md
index 4c98616..4a855e9 100644
--- a/samples/colab/README.md
+++ b/samples/colab/README.md
@@ -7,13 +7,13 @@
 
 Framework | Notebook file | Description | Link
 --------  | ------------- | ----------- | ----
-Generic | [low_level_invoke_function\.ipynb](low_level_invoke_function.ipynb) | Shows off some concepts of the low level IREE python bindings | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/low_level_invoke_function.ipynb)
-PyTorch | [pytorch_jit\.ipynb](pytorch_jit.ipynb) | Uses [SHARK-Turbine](https://github.com/nod-ai/SHARK-Turbine) for eager execution in a PyTorch session | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/pytorch_jit.ipynb)
-TensorFlow | [edge_detection\.ipynb](edge_detection.ipynb) |Performs image edge detection using TF and IREE | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/edge_detection.ipynb)
-TensorFlow | [mnist_training\.ipynb](mnist_training.ipynb) | Compile, train, and execute a neural network with IREE | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/mnist_training.ipynb)
-TensorFlow | [resnet\.ipynb](resnet.ipynb) | Loads a pretrained [ResNet50](https://www.tensorflow.org/api_docs/python/tf/keras/applications/ResNet50) model and runs it using IREE | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/resnet.ipynb)
-TensorFlow | [tensorflow_hub_import\.ipynb](tensorflow_hub_import.ipynb) | Runs a pretrained [MobileNet V2](https://tfhub.dev/google/tf2-preview/mobilenet_v2/classification) model using IREE | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_hub_import.ipynb)
-TFLite | [tflite_text_classification\.ipynb](tflite_text_classification.ipynb) | Runs a pretrained [text classification](https://www.tensorflow.org/lite/examples/text_classification/overview) model using IREE | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tflite_text_classification.ipynb)
+Generic | [low_level_invoke_function](low_level_invoke_function.ipynb) | Shows low level IREE python binding concepts | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/low_level_invoke_function.ipynb)
+PyTorch | [pytorch_jit](pytorch_jit.ipynb) | Uses [SHARK-Turbine](https://github.com/nod-ai/SHARK-Turbine) for eager execution in a PyTorch session | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/pytorch_jit.ipynb)
+TensorFlow | [tensorflow_edge_detection](tensorflow_edge_detection.ipynb) |Performs image edge detection | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_edge_detection.ipynb)
+TensorFlow | [tensorflow_hub_import](tensorflow_hub_import.ipynb) | Imports a [MobileNet V2](https://tfhub.dev/google/tf2-preview/mobilenet_v2/classification) model from [TensorFlow Hub](https://tfhub.dev/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_hub_import.ipynb)
+TensorFlow | [tensorflow_mnist_training](tensorflow_mnist_training.ipynb) | Compiles, trains, and executes a neural network | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_mnist_training.ipynb)
+TensorFlow | [tensorflow_resnet](tensorflow_resnet.ipynb) | Compiles and runs a pretrained [ResNet50](https://www.tensorflow.org/api_docs/python/tf/keras/applications/ResNet50) model | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tensorflow_resnet.ipynb)
+TFLite | [tflite_text_classification](tflite_text_classification.ipynb) | Compiles and runs a pretrained [text classification](https://www.tensorflow.org/lite/examples/text_classification/overview) model | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openxla/iree/blob/main/samples/colab/tflite_text_classification.ipynb)
 
 ## Working with GitHub
 
diff --git a/samples/colab/edge_detection.ipynb b/samples/colab/tensorflow_edge_detection.ipynb
similarity index 99%
rename from samples/colab/edge_detection.ipynb
rename to samples/colab/tensorflow_edge_detection.ipynb
index 17f8e98..7c76acc 100644
--- a/samples/colab/edge_detection.ipynb
+++ b/samples/colab/tensorflow_edge_detection.ipynb
@@ -3,7 +3,7 @@
   "nbformat_minor": 0,
   "metadata": {
     "colab": {
-      "name": "edge_detection.ipynb",
+      "name": "tensorflow_edge_detection.ipynb",
       "provenance": [],
       "collapsed_sections": [
         "FH3IRpYTta2v"
diff --git a/samples/colab/mnist_training.ipynb b/samples/colab/tensorflow_mnist_training.ipynb
similarity index 99%
rename from samples/colab/mnist_training.ipynb
rename to samples/colab/tensorflow_mnist_training.ipynb
index f7d3fab..de2ef3e 100644
--- a/samples/colab/mnist_training.ipynb
+++ b/samples/colab/tensorflow_mnist_training.ipynb
@@ -3,7 +3,7 @@
   "nbformat_minor": 0,
   "metadata": {
     "colab": {
-      "name": "mnist_training.ipynb",
+      "name": "tensorflow_mnist_training.ipynb",
       "provenance": []
     },
     "kernelspec": {
diff --git a/samples/colab/resnet.ipynb b/samples/colab/tensorflow_resnet.ipynb
similarity index 99%
rename from samples/colab/resnet.ipynb
rename to samples/colab/tensorflow_resnet.ipynb
index fe7e1dc..da8d6c1 100644
--- a/samples/colab/resnet.ipynb
+++ b/samples/colab/tensorflow_resnet.ipynb
@@ -3,7 +3,7 @@
   "nbformat_minor": 0,
   "metadata": {
     "colab": {
-      "name": "resnet.ipynb",
+      "name": "tensorflow_resnet.ipynb",
       "provenance": [],
       "collapsed_sections": [
         "FH3IRpYTta2v"
diff --git a/samples/models/mnist.mlir b/samples/models/mnist.mlir
index 98a2190..6d01a02 100644
--- a/samples/models/mnist.mlir
+++ b/samples/models/mnist.mlir
@@ -1,5 +1,5 @@
 // Trained MNIST model generated by
-// https://github.com/openxla/iree/blob/main/samples/colab/mnist_training.ipynb.
+// https://github.com/openxla/iree/blob/main/samples/colab/tensorflow_mnist_training.ipynb.
 //
 // Model structure is from tf.keras:
 //
diff --git a/tests/e2e/models/edge_detection.mlir b/tests/e2e/models/edge_detection.mlir
index 862b26b..59726ba 100644
--- a/tests/e2e/models/edge_detection.mlir
+++ b/tests/e2e/models/edge_detection.mlir
@@ -4,7 +4,7 @@
 // RUN: [[ $IREE_METAL_DISABLE == 1 ]] || (iree-run-mlir --Xcompiler,iree-input-type=stablehlo --Xcompiler,iree-hal-target-backends=metal-spirv %s --input=1x128x128x1xf32 | FileCheck %s)
 
 // Image edge detection module generated by.
-// https://github.com/openxla/iree/blob/main/samples/colab/edge_detection.ipynb.
+// https://github.com/openxla/iree/blob/main/samples/colab/tensorflow_edge_detection.ipynb.
 //
 // Input : a single 128x128 pixel image as a tensor<1x128x128x1xf32>, with pixels in [0.0, 1.0]
 // Output: a single image in the same format after running edge detection