chore: lint code and text in integration tutorials #1167
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mdlinville
reviewed
Mar 17, 2025
| {{< img src="/images/tutorials/huggingface.png" alt="" >}} | ||
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| {{< cta-button colabLink="https://colab.research.google.com/github/wandb/examples/blob/master/colabs/huggingface/Huggingface_wandb.ipynb" >}} | ||
| Visualize your [Hugging Face](https://github.com/huggingface/transformers) model's performance quickly with a seamless [W&B](https://wandb.ai/site) integration. | ||
| Visualize your [Hugging Face](https://github.com/huggingface/transformers) |
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Can you please undo the hard line wrapping that is introduced in this PR? Markdown is easier to maintain and review with soft wrapping per paragraph.
| ```notebook | ||
| # the run_glue.py script requires transformers dev | ||
| !pip install -q git+https://github.com/huggingface/transformers | ||
| ``` | ||
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| Before continuing, [sign up for a free account](https://app.wandb.ai/login?signup=true). | ||
| Before continuing, | ||
| [sign up for a free account](https://app.wandb.ai/login?signup=true). | ||
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| ## Put in your API key |
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| ## Put in your API key | |
| ## Populate your API key |
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| Optionally, we can set environment variables to customize W&B logging. See | ||
| [documentation]({{< relref "/guides/integrations/huggingface/" >}}). |
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| Optionally, we can set environment variables to customize W&B logging. See | |
| [documentation]({{< relref "/guides/integrations/huggingface/" >}}). | |
| To customize W&B logging by setting environment variables, refer to the [Hugging Face documentation]({{< relref "/guides/integrations/huggingface/" >}}). |
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| ```python | ||
| ```jupyter |
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| ```jupyter | |
| ```notebook |
Also elsewhere in this PR
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| ## Setup and Installation | ||
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| First, let us install the latest version of Weights and Biases. We will then authenticate this colab instance to use W&B. | ||
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| First, let us install the latest version of Weights and Biases. We will then |
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| First, let us install the latest version of Weights and Biases. We will then | |
| In the notebook, install Weights and Biases and sign in. |
It's better to avoid "let us" and "we" in favor of the simple imperative. I believe both of these code blocks should be tagged up as notebooks.
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| Use of proper config system is a recommended best practice for reproducible | ||
| machine learning. We can track the hyperparameters for every experiment using | ||
| W&B. In this colab we will be using simple Python `dict` as our config system. |
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| Use of proper config system is a recommended best practice for reproducible | |
| machine learning. We can track the hyperparameters for every experiment using | |
| W&B. In this colab we will be using simple Python `dict` as our config system. | |
| To reproduce a machine learning experiment, it's important to save the hyperparameters that the experiment uses. This example shows how to track an experiment's hyperparameters in a Python `dict`. |
This sentence is very hard for me to understand (not due to your changes). Here is my attempt to help, which may in fact be incorrect.
| {{< img src="/images/tutorials/huggingface-why.png" alt="" >}} | ||
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| This Colab notebook introduces the `WandbModelCheckpoint` callback. Use this callback to log your model checkpoints to Weight and Biases [Artifacts]({{< relref "/guides/core/artifacts/" >}}). | ||
| This notebook introduces the `WandbModelCheckpoint` callback. Use this callback |
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| This notebook introduces the `WandbModelCheckpoint` callback. Use this callback | |
| This notebook demonstrates how to use the `WandbModelCheckpoint` callback |
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| This Colab notebook introduces the `WandbModelCheckpoint` callback. Use this callback to log your model checkpoints to Weight and Biases [Artifacts]({{< relref "/guides/core/artifacts/" >}}). | ||
| This notebook introduces the `WandbModelCheckpoint` callback. Use this callback | ||
| to log your model checkpoints to Weight and Biases |
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| to log your model checkpoints to Weight and Biases | |
| to log your model checkpoints to W&B |
| This Colab notebook introduces the `WandbModelCheckpoint` callback. Use this callback to log your model checkpoints to Weight and Biases [Artifacts]({{< relref "/guides/core/artifacts/" >}}). | ||
| This notebook introduces the `WandbModelCheckpoint` callback. Use this callback | ||
| to log your model checkpoints to Weight and Biases | ||
| [Artifacts]({{< relref "/guides/core/artifacts/" >}}). |
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| [Artifacts]({{< relref "/guides/core/artifacts/" >}}). | |
| [artifacts]({{< relref "/guides/core/artifacts/" >}}). |
I believe we capitalize only the Python API object.
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| ## Setup and Installation | ||
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| First, let us install the latest version of Weights and Biases. We will then authenticate this colab instance to use W&B. | ||
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| First, let us install the latest version of Weights and Biases and authenticate. |
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The same feedback as in the Hugging Face example for similar changes here and in the following pages.
mdlinville
requested changes
Mar 17, 2025
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...what's in a name.