Merge pull request #10 from cleanlab/hf-torch-nbs

Updated colab links
cleanlab · Apr 11, 2023 · 398af76 · 398af76
2 parents 3b69cff + 91865e3
commit 398af76
Show file tree

Hide file tree

Showing 2 changed files with 2 additions and 30 deletions.
diff --git a/huggingface_dataset.ipynb b/huggingface_dataset.ipynb
@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cleanlab/cleanvision/blob/main/examples/huggingface_dataset.ipynb) "
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cleanlab/cleanvision-examples/blob/main/huggingface_dataset.ipynb) "
    ]
   },
   {

diff --git a/torchvision_dataset.ipynb b/torchvision_dataset.ipynb
@@ -2,24 +2,21 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "8fa4a083-1a56-419f-9e3f-fa93acd45405",
    "metadata": {},
    "source": [
     "# Run CleanVision on Torchvision dataset"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "6c52419e-f8d7-4f73-8a5d-c6d5cf90fa77",
    "metadata": {},
    "source": [
-    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cleanlab/cleanvision/blob/main/examples/torchvision_dataset.ipynb) "
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cleanlab/cleanvision-examples/blob/main/torchvision_dataset.ipynb) "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3381332c-2220-48ea-9b8a-8f974c4d5460",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -29,7 +26,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dfcd1327-924c-47ae-834d-3b9d922800f4",
    "metadata": {
     "tags": []
    },
@@ -40,7 +36,6 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "50a8cd5a-899e-4a58-84f7-fb1ddf4bfcf2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +46,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7dcf23f9-c031-4bdf-b63c-5eb02003321b",
    "metadata": {},
    "source": [
     "### Download dataset and concatenate all splits\n",
@@ -66,7 +60,6 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "79ae476e-b1dd-40d3-925e-d570c5237110",
    "metadata": {},
    "outputs": [
     {
@@ -85,7 +78,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42add096-2ad2-4e0d-8f41-2ed1f8558fbf",
    "metadata": {
     "tags": []
    },
@@ -96,7 +88,6 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "2801693b-48a3-4797-8d41-1956b9259076",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -105,7 +96,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "287a2e90-9f9b-4e6a-adde-a454430889d3",
    "metadata": {
     "tags": []
    },
@@ -116,7 +106,6 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "e159ebe1-b5ca-46ca-abf3-9a5e77db0830",
    "metadata": {},
    "outputs": [
     {
@@ -136,7 +125,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3a86c8ad-884b-425c-a538-569fa5b8e540",
    "metadata": {},
    "source": [
     "Let's look at the first image in this dataset"
@@ -145,7 +133,6 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "3a8ee57f-9542-4458-8eb4-7ebc96ed8cc0",
    "metadata": {},
    "outputs": [
     {
@@ -166,7 +153,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f5f79ba0-3ef0-4ba9-8d85-726ee534bfc8",
    "metadata": {},
    "source": [
     "### Run CleanVision"
@@ -175,7 +161,6 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "92c32767-ddd3-4881-853b-c0bee34cf94e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -184,7 +169,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e0fe56ff-35d7-49d2-a99f-f867d1cfe376",
    "metadata": {},
    "source": [
     "We set `n_jobs = 1` as CleanVision parallelization may interact with torch dataloaders in unexpected ways."
@@ -193,7 +177,6 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "71df74ca-63ee-48f2-bdd0-c335f17c96f8",
    "metadata": {},
    "outputs": [
     {
@@ -225,7 +208,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3e2c1bc7-3042-4e8a-91f9-2a7840e03255",
    "metadata": {
     "tags": []
    },
@@ -236,7 +218,6 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "779adbac-7dde-463a-b6d2-4afc872f31b2",
    "metadata": {},
    "outputs": [
     {
@@ -377,7 +358,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f64b1e8b-97f2-4ae3-913d-699541fa9ab6",
    "metadata": {},
    "source": [
     "View more information about each image, such as what types of issues it exhibits and its quality score with respect to each type of issue."
@@ -386,7 +366,6 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "1a7bce39-a072-4284-b7e6-2b12c55949e8",
    "metadata": {},
    "outputs": [
     {
@@ -699,7 +678,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a9d4c1eb-bbf7-471c-b057-6161c8ac45ae",
    "metadata": {},
    "source": [
     "Get indices of all **dark** images in the dataset sorted by their dark score."
@@ -708,7 +686,6 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "c54d1234-c076-4e07-bc4a-e8610f0d27bf",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -717,7 +694,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d7f241fc-0674-49af-ac59-c2cde1a79b3f",
    "metadata": {},
    "source": [
     "View the 5th darkest image in the dataset"
@@ -726,7 +702,6 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "345a9996-850b-492e-ba45-afde3c1ca64e",
    "metadata": {},
    "outputs": [
     {
@@ -747,7 +722,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9efed1a8-3a2d-4f2b-9470-f8196a3d5791",
    "metadata": {},
    "source": [
     "View global information about each issue, such as how many images in the dataset suffer from this issue."
@@ -756,7 +730,6 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "9f47f3b1-41d2-41cb-8816-25ae16ce2b29",
    "metadata": {},
    "outputs": [
     {
@@ -852,7 +825,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24c4ef0e-fb94-45c6-a76e-c74825c1b214",
    "metadata": {},
    "source": [
     "**For more detailed guide on how to use CleanVision, check the [tutorial notebook](https://github.com/cleanlab/cleanvision/blob/main/examples/tutorial.ipynb).**"