From 321ccce6b7001e318bebc052382d0518f1f9e3e1 Mon Sep 17 00:00:00 2001 From: vinid Date: Tue, 11 Jun 2024 23:10:33 -0400 Subject: [PATCH] update badges in notebooks --- examples/notebooks/Primitives.ipynb | 96 +++++-------------- examples/notebooks/Prompt-Optimization.ipynb | 26 ++--- .../Tutorial-Solution-Optimization.ipynb | 16 ++-- .../Tutorial-Test-Time-Loss-for-Code.ipynb | 6 +- 4 files changed, 44 insertions(+), 100 deletions(-) diff --git a/examples/notebooks/Primitives.ipynb b/examples/notebooks/Primitives.ipynb index 479b5db..d559731 100644 --- a/examples/notebooks/Primitives.ipynb +++ b/examples/notebooks/Primitives.ipynb @@ -11,8 +11,12 @@ "\n", "An autograd engine -- for textual gradients!\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](LINK)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zou-group/TextGrad/blob/main/examples/notebooks/Prompt-Optimization.ipynb)\n", "[![GitHub license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)\n", + "[![Arxiv](https://img.shields.io/badge/arXiv-2406.07496-B31B1B.svg)](https://arxiv.org/abs/2406.07496)\n", + "[![Documentation Status](https://readthedocs.org/projects/textgrad/badge/?version=latest)](https://textgrad.readthedocs.io/en/latest/?badge=latest)\n", + "[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/textgrad)](https://pypi.org/project/textgrad/)\n", + "[![PyPI](https://img.shields.io/pypi/v/textgrad)](https://pypi.org/project/textgrad/)\n", "\n", "**Objectives for this tutorial:**\n", "\n", @@ -59,10 +63,7 @@ "cell_type": "markdown", "id": "8887fbed36c7daf2", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Introduction: Variable\n", @@ -87,10 +88,7 @@ "end_time": "2024-06-11T15:43:17.669096228Z", "start_time": "2024-06-11T15:43:17.665325560Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -106,10 +104,7 @@ "end_time": "2024-06-11T15:43:18.184004948Z", "start_time": "2024-06-11T15:43:18.178187640Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -131,10 +126,7 @@ "cell_type": "markdown", "id": "63f6a6921a1cce6a", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Introduction: Engine\n", @@ -151,10 +143,7 @@ "end_time": "2024-06-11T15:44:32.606319032Z", "start_time": "2024-06-11T15:44:32.561460448Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -165,10 +154,7 @@ "cell_type": "markdown", "id": "33c7d6eaa115cd6a", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "This object behaves like you would expect an LLM to behave: You can sample generation from the engine using the `generate` method. " @@ -183,10 +169,7 @@ "end_time": "2024-06-11T17:29:41.108552705Z", "start_time": "2024-06-11T17:29:40.294256814Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -208,10 +191,7 @@ "cell_type": "markdown", "id": "b627edc07c0d3737", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Introduction: Loss\n", @@ -228,10 +208,7 @@ "end_time": "2024-06-11T15:44:32.894722136Z", "start_time": "2024-06-11T15:44:32.890708561Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -243,10 +220,7 @@ "cell_type": "markdown", "id": "ff137c99e0659dcc", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [] }, @@ -254,10 +228,7 @@ "cell_type": "markdown", "id": "6f05ec2bf907b3ba", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Introduction: Optimizer\n", @@ -276,10 +247,7 @@ "end_time": "2024-06-11T15:44:33.741130951Z", "start_time": "2024-06-11T15:44:33.734977769Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -290,10 +258,7 @@ "cell_type": "markdown", "id": "d26883eb74ce0d01", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Putting it all together\n", @@ -310,10 +275,7 @@ "end_time": "2024-06-11T15:44:41.730132530Z", "start_time": "2024-06-11T15:44:34.997777872Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -331,10 +293,7 @@ "end_time": "2024-06-11T15:44:41.738985151Z", "start_time": "2024-06-11T15:44:41.731989729Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [ { @@ -356,10 +315,7 @@ "cell_type": "markdown", "id": "6a8aab93b80fb82c", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "While here it is not going to be useful, we can also do multiple optimization steps in a loop! Do not forget to reset the gradients after each step!" @@ -373,10 +329,7 @@ "ExecuteTime": { "start_time": "2024-06-11T15:44:30.989940227Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -388,10 +341,7 @@ "execution_count": null, "id": "a3a84aad4cd58737", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [] diff --git a/examples/notebooks/Prompt-Optimization.ipynb b/examples/notebooks/Prompt-Optimization.ipynb index 2bb48dd..b689d93 100644 --- a/examples/notebooks/Prompt-Optimization.ipynb +++ b/examples/notebooks/Prompt-Optimization.ipynb @@ -11,8 +11,12 @@ "\n", "An autograd engine -- for textual gradients!\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](LINK)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zou-group/TextGrad/blob/main/examples/notebooks/Prompt-Optimization.ipynb)\n", "[![GitHub license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)\n", + "[![Arxiv](https://img.shields.io/badge/arXiv-2406.07496-B31B1B.svg)](https://arxiv.org/abs/2406.07496)\n", + "[![Documentation Status](https://readthedocs.org/projects/textgrad/badge/?version=latest)](https://textgrad.readthedocs.io/en/latest/?badge=latest)\n", + "[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/textgrad)](https://pypi.org/project/textgrad/)\n", + "[![PyPI](https://img.shields.io/pypi/v/textgrad)](https://pypi.org/project/textgrad/)\n", "\n", "**Objectives:**\n", "\n", @@ -74,10 +78,7 @@ "end_time": "2024-06-11T19:30:42.098338405Z", "start_time": "2024-06-11T19:30:42.093473103Z" }, - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -91,10 +92,7 @@ "execution_count": 9, "id": "649e06aef34d0990", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -121,10 +119,7 @@ "execution_count": 10, "id": "9559a31e07e54d7f", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ @@ -153,10 +148,7 @@ "execution_count": 11, "id": "4ea732b7edf34eb9", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ diff --git a/examples/notebooks/Tutorial-Solution-Optimization.ipynb b/examples/notebooks/Tutorial-Solution-Optimization.ipynb index 57b7b1f..f55b611 100644 --- a/examples/notebooks/Tutorial-Solution-Optimization.ipynb +++ b/examples/notebooks/Tutorial-Solution-Optimization.ipynb @@ -4,10 +4,7 @@ "cell_type": "markdown", "id": "fe4cb25e4fb45586", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "source": [ "## Tutorial: Running Solution Optimization\n", @@ -16,8 +13,12 @@ "\n", "An autograd engine -- for textual gradients!\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](LINK)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zou-group/TextGrad/blob/main/examples/notebooks/Prompt-Optimization.ipynb)\n", "[![GitHub license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)\n", + "[![Arxiv](https://img.shields.io/badge/arXiv-2406.07496-B31B1B.svg)](https://arxiv.org/abs/2406.07496)\n", + "[![Documentation Status](https://readthedocs.org/projects/textgrad/badge/?version=latest)](https://textgrad.readthedocs.io/en/latest/?badge=latest)\n", + "[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/textgrad)](https://pypi.org/project/textgrad/)\n", + "[![PyPI](https://img.shields.io/pypi/v/textgrad)](https://pypi.org/project/textgrad/)\n", "\n", "**Objectives:**\n", "\n", @@ -33,10 +34,7 @@ "execution_count": null, "id": "1f6e021565d0c914", "metadata": { - "collapsed": false, - "jupyter": { - "outputs_hidden": false - } + "collapsed": false }, "outputs": [], "source": [ diff --git a/examples/notebooks/Tutorial-Test-Time-Loss-for-Code.ipynb b/examples/notebooks/Tutorial-Test-Time-Loss-for-Code.ipynb index be16f89..4305a13 100644 --- a/examples/notebooks/Tutorial-Test-Time-Loss-for-Code.ipynb +++ b/examples/notebooks/Tutorial-Test-Time-Loss-for-Code.ipynb @@ -11,8 +11,12 @@ "\n", "An autograd engine -- for textual gradients!\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](LINK)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zou-group/TextGrad/blob/main/examples/notebooks/Prompt-Optimization.ipynb)\n", "[![GitHub license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)\n", + "[![Arxiv](https://img.shields.io/badge/arXiv-2406.07496-B31B1B.svg)](https://arxiv.org/abs/2406.07496)\n", + "[![Documentation Status](https://readthedocs.org/projects/textgrad/badge/?version=latest)](https://textgrad.readthedocs.io/en/latest/?badge=latest)\n", + "[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/textgrad)](https://pypi.org/project/textgrad/)\n", + "[![PyPI](https://img.shields.io/pypi/v/textgrad)](https://pypi.org/project/textgrad/)\n", "\n", "**Objectives:**\n", "\n",