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user-guide: document Hugging Face Storage Buckets as a remote #5595

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user-guide: document Hugging Face Storage Buckets as a remote
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28 changes: 28 additions & 0 deletions content/docs/user-guide/integrations/huggingface.md
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Expand Up @@ -76,6 +76,34 @@ into a <abbr>DVC project</abbr>:
$ dvc import https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 sd_xl_base_1.0.safetensors
```

## Hugging Face Storage Buckets

[Storage Buckets](https://huggingface.co/docs/hub/storage-buckets) are mutable
object storage on the Hugging Face Hub with an
[S3-compatible API](https://huggingface.co/docs/hub/storage-buckets-s3), so a
bucket can be used as a DVC
[remote](/doc/user-guide/data-management/remote-storage/amazon-s3). Set
`endpointurl` to `https://s3.hf.co/<NAMESPACE>` (your Hugging Face user or
organization name) and use the bare bucket name in the `s3://` URL:

```cli
$ pip install "dvc[s3]"
$ dvc remote add -d myremote s3://<BUCKET>/dvc-store
$ dvc remote modify myremote endpointurl https://s3.hf.co/<NAMESPACE>
$ dvc remote modify myremote region us-east-1
```

Generate S3 credentials for the bucket in your
[Hugging Face settings](https://huggingface.co/docs/hub/storage-buckets-s3#generating-s3-credentials)
and set them with `dvc remote modify --local` so they stay out of Git:

```cli
$ dvc remote modify --local myremote access_key_id <ACCESS_KEY_ID>
$ dvc remote modify --local myremote secret_access_key <SECRET_ACCESS_KEY>
```

`dvc push` and `dvc pull` then work as with any S3 remote.

## Hugging Face Datasets

[Hugging Face Datasets](https://huggingface.co/docs/datasets/index) is a Python
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