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name, open in colab and tracker
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tcapelle committed Aug 9, 2024
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56 changes: 37 additions & 19 deletions colabs/wandb_registry/zoo_wandb.ipynb
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"cells": [
{
"cell_type": "markdown",
"id": "381c6d14-e10d-4996-bd01-e743208644d6",
"id": "d24dab37",
"metadata": {},
"source": [
"<a href=\"https://colab.research.google.com/github/wandb/examples/blob/master/colabs/wandb_registry/zoo_wandb.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
"<!--- @wandbcode{zoo-wandb} -->"
]
},
{
"cell_type": "markdown",
"id": "d75eb97c",
"metadata": {},
"source": [
"<img src=\"http://wandb.me/logo-im-png\" width=\"400\" alt=\"Weights & Biases\" />\n",
"\n",
"<!--- @wandbcode{zoo-wandb} -->"
]
},
{
"cell_type": "markdown",
"id": "2f7e5952",
"metadata": {},
"source": [
"# Weights & Biases Registry Tutorial"
]
},
{
"cell_type": "markdown",
"id": "507ab87f",
"metadata": {},
"source": [
"The goal of this notebook is to demonstrate how you and other members of your organization can use W&B Registry to track, share, and use dataset and model artifacts in your machine learning workflows. By the end of this notebook, you will know how to use W&B to:\n",
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"cell_type": "code",
"execution_count": null,
"id": "1042375b-c2c8-4503-9888-a406bc9c5df1",
"metadata": {
"scrolled": true
},
"metadata": {},
"outputs": [],
"source": [
"run = wandb.init(entity = TEAM_ENTITY, project = PROJECT, job_type = \"training\", config = hyperparameter_config)\n",
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}
],
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