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/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | <!--⚠️ Note that this file is in Markdown but contains specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
--> | 37_0_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | The `huggingface_hub` library provides functions to download files from the repositories
stored on the Hub. You can use these functions independently or integrate them into your
own library, making it more convenient for your users to interact with the Hub. This
guide will show you how to:
* Download and cache a single file.
* Download and cache an entire repository.
* Download files to a local folder. | 37_1_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | The [`hf_hub_download`] function is the main function for downloading files from the Hub.
It downloads the remote file, caches it on disk (in a version-aware way), and returns its local file path.
<Tip>
The returned filepath is a pointer to the HF local cache. Therefore, it is important to not modify the file to avoid
having a corrupted cache. If you are interested in getting to know more about how files are cached, please refer to our
[caching guide](./manage-cache).
</Tip> | 37_2_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | Select the file to download using the `repo_id`, `repo_type` and `filename` parameters. By default, the file will
be considered as being part of a `model` repo.
```python
>>> from huggingface_hub import hf_hub_download
>>> hf_hub_download(repo_id="lysandre/arxiv-nlp", filename="config.json")
'/root/.cache/huggingface/hub/models--lysandre--arxiv-nlp/snapshots/894a9adde21d9a3e3843e6d5aeaaf01875c7fade/config.json' | 37_3_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | # Download from a dataset
>>> hf_hub_download(repo_id="google/fleurs", filename="fleurs.py", repo_type="dataset")
'/root/.cache/huggingface/hub/datasets--google--fleurs/snapshots/199e4ae37915137c555b1765c01477c216287d34/fleurs.py'
``` | 37_3_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | By default, the latest version from the `main` branch is downloaded. However, in some cases you want to download a file
at a particular version (e.g. from a specific branch, a PR, a tag or a commit hash).
To do so, use the `revision` parameter:
```python
# Download from the `v1.0` tag
>>> hf_hub_download(repo_id="lysandre/arxiv-nlp", filename="config.json", revision="v1.0") | 37_4_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | # Download from the `test-branch` branch
>>> hf_hub_download(repo_id="lysandre/arxiv-nlp", filename="config.json", revision="test-branch")
# Download from Pull Request #3
>>> hf_hub_download(repo_id="lysandre/arxiv-nlp", filename="config.json", revision="refs/pr/3") | 37_4_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | # Download from a specific commit hash
>>> hf_hub_download(repo_id="lysandre/arxiv-nlp", filename="config.json", revision="877b84a8f93f2d619faa2a6e514a32beef88ab0a")
```
**Note:** When using the commit hash, it must be the full-length hash instead of a 7-character commit hash. | 37_4_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | In case you want to construct the URL used to download a file from a repo, you can use [`hf_hub_url`] which returns a URL.
Note that it is used internally by [`hf_hub_download`]. | 37_5_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | [`snapshot_download`] downloads an entire repository at a given revision. It uses internally [`hf_hub_download`] which
means all downloaded files are also cached on your local disk. Downloads are made concurrently to speed-up the process.
To download a whole repository, just pass the `repo_id` and `repo_type`:
```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="lysandre/arxiv-nlp") | 37_6_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | ```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="lysandre/arxiv-nlp")
'/home/lysandre/.cache/huggingface/hub/models--lysandre--arxiv-nlp/snapshots/894a9adde21d9a3e3843e6d5aeaaf01875c7fade' | 37_6_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | # Or from a dataset
>>> snapshot_download(repo_id="google/fleurs", repo_type="dataset")
'/home/lysandre/.cache/huggingface/hub/datasets--google--fleurs/snapshots/199e4ae37915137c555b1765c01477c216287d34'
```
[`snapshot_download`] downloads the latest revision by default. If you want a specific repository revision, use the
`revision` parameter:
```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="lysandre/arxiv-nlp", revision="refs/pr/1")
``` | 37_6_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | [`snapshot_download`] provides an easy way to download a repository. However, you don't always want to download the
entire content of a repository. For example, you might want to prevent downloading all `.bin` files if you know you'll
only use the `.safetensors` weights. You can do that using `allow_patterns` and `ignore_patterns` parameters.
These parameters accept either a single pattern or a list of patterns. Patterns are Standard Wildcards (globbing | 37_7_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | These parameters accept either a single pattern or a list of patterns. Patterns are Standard Wildcards (globbing
patterns) as documented [here](https://tldp.org/LDP/GNU-Linux-Tools-Summary/html/x11655.htm). The pattern matching is
based on [`fnmatch`](https://docs.python.org/3/library/fnmatch.html).
For example, you can use `allow_patterns` to only download JSON configuration files:
```python
>>> from huggingface_hub import snapshot_download | 37_7_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | ```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="lysandre/arxiv-nlp", allow_patterns="*.json")
```
On the other hand, `ignore_patterns` can exclude certain files from being downloaded. The
following example ignores the `.msgpack` and `.h5` file extensions:
```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="lysandre/arxiv-nlp", ignore_patterns=["*.msgpack", "*.h5"])
``` | 37_7_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | >>> snapshot_download(repo_id="lysandre/arxiv-nlp", ignore_patterns=["*.msgpack", "*.h5"])
```
Finally, you can combine both to precisely filter your download. Here is an example to download all json and markdown
files except `vocab.json`.
```python
>>> from huggingface_hub import snapshot_download
>>> snapshot_download(repo_id="gpt2", allow_patterns=["*.md", "*.json"], ignore_patterns="vocab.json")
``` | 37_7_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | By default, we recommend using the [cache system](./manage-cache) to download files from the Hub. You can specify a custom cache location using the `cache_dir` parameter in [`hf_hub_download`] and [`snapshot_download`], or by setting the [`HF_HOME`](../package_reference/environment_variables#hf_home) environment variable. | 37_8_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | However, if you need to download files to a specific folder, you can pass a `local_dir` parameter to the download function. This is useful to get a workflow closer to what the `git` command offers. The downloaded files will maintain their original file structure within the specified folder. For example, if `filename="data/train.csv"` and `local_dir="path/to/folder"`, the resulting filepath will be `"path/to/folder/data/train.csv"`. | 37_8_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | A `.cache/huggingface/` folder is created at the root of your local directory containing metadata about the downloaded files. This prevents re-downloading files if they're already up-to-date. If the metadata has changed, then the new file version is downloaded. This makes the `local_dir` optimized for pulling only the latest changes. | 37_8_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | After completing the download, you can safely remove the `.cache/huggingface/` folder if you no longer need it. However, be aware that re-running your script without this folder may result in longer recovery times, as metadata will be lost. Rest assured that your local data will remain intact and unaffected.
<Tip>
Don't worry about the `.cache/huggingface/` folder when committing changes to the Hub! This folder is automatically ignored by both `git` and [`upload_folder`].
</Tip> | 37_8_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | You can use the `huggingface-cli download` command from the terminal to directly download files from the Hub.
Internally, it uses the same [`hf_hub_download`] and [`snapshot_download`] helpers described above and prints the
returned path to the terminal.
```bash
>>> huggingface-cli download gpt2 config.json
/home/wauplin/.cache/huggingface/hub/models--gpt2/snapshots/11c5a3d5811f50298f278a704980280950aedb10/config.json
``` | 37_9_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | /home/wauplin/.cache/huggingface/hub/models--gpt2/snapshots/11c5a3d5811f50298f278a704980280950aedb10/config.json
```
You can download multiple files at once which displays a progress bar and returns the snapshot path in which the files
are located:
```bash
>>> huggingface-cli download gpt2 config.json model.safetensors
Fetching 2 files: 100%|████████████████████████████████████████████| 2/2 [00:00<00:00, 23831.27it/s] | 37_9_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | Fetching 2 files: 100%|████████████████████████████████████████████| 2/2 [00:00<00:00, 23831.27it/s]
/home/wauplin/.cache/huggingface/hub/models--gpt2/snapshots/11c5a3d5811f50298f278a704980280950aedb10
```
For more details about the CLI download command, please refer to the [CLI guide](./cli#huggingface-cli-download). | 37_9_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | If you are running on a machine with high bandwidth,
you can increase your download speed with [`hf_transfer`](https://github.com/huggingface/hf_transfer),
a Rust-based library developed to speed up file transfers with the Hub.
To enable it:
1. Specify the `hf_transfer` extra when installing `huggingface_hub`
(e.g. `pip install huggingface_hub[hf_transfer]`).
2. Set `HF_HUB_ENABLE_HF_TRANSFER=1` as an environment variable.
<Tip warning={true}>
`hf_transfer` is a power user tool! | 37_10_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/download.md | .md | 2. Set `HF_HUB_ENABLE_HF_TRANSFER=1` as an environment variable.
<Tip warning={true}>
`hf_transfer` is a power user tool!
It is tested and production-ready,
but it lacks user-friendly features like advanced error handling or proxies.
For more details, please take a look at this [section](https://huggingface.co/docs/huggingface_hub/hf_transfer).
</Tip> | 37_10_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | <!--⚠️ Note that this file is in Markdown but contains specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
--> | 38_0_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The Hugging Face Hub cache-system is designed to be the central cache shared across libraries
that depend on the Hub. It has been updated in v0.8.0 to prevent re-downloading same files
between revisions.
The caching system is designed as follows:
```
<CACHE_DIR>
├─ <MODELS>
├─ <DATASETS>
├─ <SPACES>
``` | 38_1_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | between revisions.
The caching system is designed as follows:
```
<CACHE_DIR>
├─ <MODELS>
├─ <DATASETS>
├─ <SPACES>
```
The `<CACHE_DIR>` is usually your user's home directory. However, it is customizable with the `cache_dir` argument on all methods, or by specifying either `HF_HOME` or `HF_HUB_CACHE` environment variable.
Models, datasets and spaces share a common root. Each of these repositories contains the
repository type, the namespace (organization or username) if it exists and the | 38_1_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | repository type, the namespace (organization or username) if it exists and the
repository name:
```
<CACHE_DIR>
├─ models--julien-c--EsperBERTo-small
├─ models--lysandrejik--arxiv-nlp
├─ models--bert-base-cased
├─ datasets--glue
├─ datasets--huggingface--DataMeasurementsFiles
├─ spaces--dalle-mini--dalle-mini
```
It is within these folders that all files will now be downloaded from the Hub. Caching ensures that | 38_1_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ```
It is within these folders that all files will now be downloaded from the Hub. Caching ensures that
a file isn't downloaded twice if it already exists and wasn't updated; but if it was updated,
and you're asking for the latest file, then it will download the latest file (while keeping
the previous file intact in case you need it again).
In order to achieve this, all folders contain the same skeleton:
```
<CACHE_DIR>
├─ datasets--glue
│ ├─ refs
│ ├─ blobs
│ ├─ snapshots
...
``` | 38_1_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ```
<CACHE_DIR>
├─ datasets--glue
│ ├─ refs
│ ├─ blobs
│ ├─ snapshots
...
```
Each folder is designed to contain the following: | 38_1_4 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The `refs` folder contains files which indicates the latest revision of the given reference. For example,
if we have previously fetched a file from the `main` branch of a repository, the `refs`
folder will contain a file named `main`, which will itself contain the commit identifier of the current head.
If the latest commit of `main` has `aaaaaa` as identifier, then it will contain `aaaaaa`.
If that same branch gets updated with a new commit, that has `bbbbbb` as an identifier, then | 38_2_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | If that same branch gets updated with a new commit, that has `bbbbbb` as an identifier, then
re-downloading a file from that reference will update the `refs/main` file to contain `bbbbbb`. | 38_2_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The `blobs` folder contains the actual files that we have downloaded. The name of each file is their hash. | 38_3_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The `snapshots` folder contains symlinks to the blobs mentioned above. It is itself made up of several folders:
one per known revision!
In the explanation above, we had initially fetched a file from the `aaaaaa` revision, before fetching a file from
the `bbbbbb` revision. In this situation, we would now have two folders in the `snapshots` folder: `aaaaaa`
and `bbbbbb`.
In each of these folders, live symlinks that have the names of the files that we have downloaded. For example, | 38_4_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | and `bbbbbb`.
In each of these folders, live symlinks that have the names of the files that we have downloaded. For example,
if we had downloaded the `README.md` file at revision `aaaaaa`, we would have the following path:
```
<CACHE_DIR>/<REPO_NAME>/snapshots/aaaaaa/README.md
```
That `README.md` file is actually a symlink linking to the blob that has the hash of the file.
By creating the skeleton this way we open the mechanism to file sharing: if the same file was fetched in | 38_4_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | By creating the skeleton this way we open the mechanism to file sharing: if the same file was fetched in
revision `bbbbbb`, it would have the same hash and the file would not need to be re-downloaded. | 38_4_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In addition to the `blobs`, `refs` and `snapshots` folders, you might also find a `.no_exist` folder
in your cache. This folder keeps track of files that you've tried to download once but don't exist
on the Hub. Its structure is the same as the `snapshots` folder with 1 subfolder per known revision:
```
<CACHE_DIR>/<REPO_NAME>/.no_exist/aaaaaa/config_that_does_not_exist.json
```
Unlike the `snapshots` folder, files are simple empty files (no symlinks). In this example, | 38_5_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ```
Unlike the `snapshots` folder, files are simple empty files (no symlinks). In this example,
the file `"config_that_does_not_exist.json"` does not exist on the Hub for the revision `"aaaaaa"`.
As it only stores empty files, this folder is neglectable in term of disk usage.
So now you might wonder, why is this information even relevant?
In some cases, a framework tries to load optional files for a model. Saving the non-existence | 38_5_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In some cases, a framework tries to load optional files for a model. Saving the non-existence
of optional files makes it faster to load a model as it saves 1 HTTP call per possible optional file.
This is for example the case in `transformers` where each tokenizer can support additional files.
The first time you load the tokenizer on your machine, it will cache which optional files exist (and
which doesn't) to make the loading time faster for the next initializations. | 38_5_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | which doesn't) to make the loading time faster for the next initializations.
To test if a file is cached locally (without making any HTTP request), you can use the [`try_to_load_from_cache`]
helper. It will either return the filepath (if exists and cached), the object `_CACHED_NO_EXIST` (if non-existence
is cached) or `None` (if we don't know).
```python
from huggingface_hub import try_to_load_from_cache, _CACHED_NO_EXIST | 38_5_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | filepath = try_to_load_from_cache()
if isinstance(filepath, str):
# file exists and is cached
...
elif filepath is _CACHED_NO_EXIST:
# non-existence of file is cached
...
else:
# file is not cached
...
``` | 38_5_4 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In practice, your cache should look like the following tree:
```text
[ 96] .
└── [ 160] models--julien-c--EsperBERTo-small
├── [ 160] blobs
│ ├── [321M] 403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
│ ├── [ 398] 7cb18dc9bafbfcf74629a4b760af1b160957a83e
│ └── [1.4K] d7edf6bd2a681fb0175f7735299831ee1b22b812
├── [ 96] refs
│ └── [ 40] main
└── [ 128] snapshots
├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f | 38_6_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ├── [ 96] refs
│ └── [ 40] main
└── [ 128] snapshots
├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f
│ ├── [ 52] README.md -> ../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812
│ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
└── [ 128] bbc77c8132af1cc5cf678da3f1ddf2de43606d48
├── [ 52] README.md -> ../../blobs/7cb18dc9bafbfcf74629a4b760af1b160957a83e | 38_6_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ├── [ 52] README.md -> ../../blobs/7cb18dc9bafbfcf74629a4b760af1b160957a83e
└── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
``` | 38_6_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In order to have an efficient cache-system, `huggingface-hub` uses symlinks. However,
symlinks are not supported on all machines. This is a known limitation especially on
Windows. When this is the case, `huggingface_hub` do not use the `blobs/` directory but
directly stores the files in the `snapshots/` directory instead. This workaround allows
users to download and cache files from the Hub exactly the same way. Tools to inspect | 38_7_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | users to download and cache files from the Hub exactly the same way. Tools to inspect
and delete the cache (see below) are also supported. However, the cache-system is less
efficient as a single file might be downloaded several times if multiple revisions of
the same repo is downloaded.
If you want to benefit from the symlink-based cache-system on a Windows machine, you
either need to [activate Developer Mode](https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development) | 38_7_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | or to run Python as an administrator.
When symlinks are not supported, a warning message is displayed to the user to alert
them they are using a degraded version of the cache-system. This warning can be disabled
by setting the `HF_HUB_DISABLE_SYMLINKS_WARNING` environment variable to true. | 38_7_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In addition to caching files from the Hub, downstream libraries often requires to cache
other files related to HF but not handled directly by `huggingface_hub` (example: file
downloaded from GitHub, preprocessed data, logs,...). In order to cache those files,
called `assets`, one can use [`cached_assets_path`]. This small helper generates paths
in the HF cache in a unified way based on the name of the library requesting it and | 38_8_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | in the HF cache in a unified way based on the name of the library requesting it and
optionally on a namespace and a subfolder name. The goal is to let every downstream
libraries manage its assets its own way (e.g. no rule on the structure) as long as it
stays in the right assets folder. Those libraries can then leverage tools from
`huggingface_hub` to manage the cache, in particular scanning and deleting parts of the
assets from a CLI command.
```py
from huggingface_hub import cached_assets_path | 38_8_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | assets_path = cached_assets_path(library_name="datasets", namespace="SQuAD", subfolder="download")
something_path = assets_path / "something.json" # Do anything you like in your assets folder !
```
<Tip>
[`cached_assets_path`] is the recommended way to store assets but is not mandatory. If
your library already uses its own cache, feel free to use it!
</Tip> | 38_8_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | In practice, your assets cache should look like the following tree:
```text
assets/
└── datasets/
│ ├── SQuAD/
│ │ ├── downloaded/
│ │ ├── extracted/
│ │ └── processed/
│ ├── Helsinki-NLP--tatoeba_mt/
│ ├── downloaded/
│ ├── extracted/
│ └── processed/
└── transformers/
├── default/
│ ├── something/
├── bert-base-cased/
│ ├── default/
│ └── training/
hub/
└── models--julien-c--EsperBERTo-small/
├── blobs/
│ ├── (...)
│ ├── (...)
├── refs/
│ └── (...) | 38_9_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | │ └── training/
hub/
└── models--julien-c--EsperBERTo-small/
├── blobs/
│ ├── (...)
│ ├── (...)
├── refs/
│ └── (...)
└── [ 128] snapshots/
├── 2439f60ef33a0d46d85da5001d52aeda5b00ce9f/
│ ├── (...)
└── bbc77c8132af1cc5cf678da3f1ddf2de43606d48/
└── (...)
``` | 38_9_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | At the moment, cached files are never deleted from your local directory: when you download
a new revision of a branch, previous files are kept in case you need them again.
Therefore it can be useful to scan your cache directory in order to know which repos
and revisions are taking the most disk space. `huggingface_hub` provides an helper to
do so that can be used via `huggingface-cli` or in a python script. | 38_10_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The easiest way to scan your HF cache-system is to use the `scan-cache` command from
`huggingface-cli` tool. This command scans the cache and prints a report with information
like repo id, repo type, disk usage, refs and full local path.
The snippet below shows a scan report in a folder in which 4 models and 2 datasets are
cached.
```text
➜ huggingface-cli scan-cache
REPO ID REPO TYPE SIZE ON DISK NB FILES LAST_ACCESSED LAST_MODIFIED REFS LOCAL PATH | 38_11_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | REPO ID REPO TYPE SIZE ON DISK NB FILES LAST_ACCESSED LAST_MODIFIED REFS LOCAL PATH
--------------------------- --------- ------------ -------- ------------- ------------- ------------------- -------------------------------------------------------------------------
glue dataset 116.3K 15 4 days ago 4 days ago 2.4.0, main, 1.17.0 /home/wauplin/.cache/huggingface/hub/datasets--glue | 38_11_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | google/fleurs dataset 64.9M 6 1 week ago 1 week ago refs/pr/1, main /home/wauplin/.cache/huggingface/hub/datasets--google--fleurs
Jean-Baptiste/camembert-ner model 441.0M 7 2 weeks ago 16 hours ago main /home/wauplin/.cache/huggingface/hub/models--Jean-Baptiste--camembert-ner | 38_11_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | bert-base-cased model 1.9G 13 1 week ago 2 years ago /home/wauplin/.cache/huggingface/hub/models--bert-base-cased
t5-base model 10.1K 3 3 months ago 3 months ago main /home/wauplin/.cache/huggingface/hub/models--t5-base
t5-small model 970.7M 11 3 days ago 3 days ago refs/pr/1, main /home/wauplin/.cache/huggingface/hub/models--t5-small | 38_11_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | Done in 0.0s. Scanned 6 repo(s) for a total of 3.4G.
Got 1 warning(s) while scanning. Use -vvv to print details.
```
To get a more detailed report, use the `--verbose` option. For each repo, you get a
list of all revisions that have been downloaded. As explained above, the files that don't
change between 2 revisions are shared thanks to the symlinks. This means that the size of
the repo on disk is expected to be less than the sum of the size of each of its revisions. | 38_11_4 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | the repo on disk is expected to be less than the sum of the size of each of its revisions.
For example, here `bert-base-cased` has 2 revisions of 1.4G and 1.5G but the total disk
usage is only 1.9G.
```text
➜ huggingface-cli scan-cache -v
REPO ID REPO TYPE REVISION SIZE ON DISK NB FILES LAST_MODIFIED REFS LOCAL PATH | 38_11_5 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | --------------------------- --------- ---------------------------------------- ------------ -------- ------------- ----------- ----------------------------------------------------------------------------------------------------------------------------
glue dataset 9338f7b671827df886678df2bdd7cc7b4f36dffd 97.7K 14 4 days ago main, 2.4.0 /home/wauplin/.cache/huggingface/hub/datasets--glue/snapshots/9338f7b671827df886678df2bdd7cc7b4f36dffd | 38_11_6 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | glue dataset f021ae41c879fcabcf823648ec685e3fead91fe7 97.8K 14 1 week ago 1.17.0 /home/wauplin/.cache/huggingface/hub/datasets--glue/snapshots/f021ae41c879fcabcf823648ec685e3fead91fe7
google/fleurs dataset 129b6e96cf1967cd5d2b9b6aec75ce6cce7c89e8 25.4K 3 2 weeks ago refs/pr/1 /home/wauplin/.cache/huggingface/hub/datasets--google--fleurs/snapshots/129b6e96cf1967cd5d2b9b6aec75ce6cce7c89e8 | 38_11_7 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | google/fleurs dataset 24f85a01eb955224ca3946e70050869c56446805 64.9M 4 1 week ago main /home/wauplin/.cache/huggingface/hub/datasets--google--fleurs/snapshots/24f85a01eb955224ca3946e70050869c56446805
Jean-Baptiste/camembert-ner model dbec8489a1c44ecad9da8a9185115bccabd799fe 441.0M 7 16 hours ago main /home/wauplin/.cache/huggingface/hub/models--Jean-Baptiste--camembert-ner/snapshots/dbec8489a1c44ecad9da8a9185115bccabd799fe | 38_11_8 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | bert-base-cased model 378aa1bda6387fd00e824948ebe3488630ad8565 1.5G 9 2 years ago /home/wauplin/.cache/huggingface/hub/models--bert-base-cased/snapshots/378aa1bda6387fd00e824948ebe3488630ad8565
bert-base-cased model a8d257ba9925ef39f3036bfc338acf5283c512d9 1.4G 9 3 days ago main /home/wauplin/.cache/huggingface/hub/models--bert-base-cased/snapshots/a8d257ba9925ef39f3036bfc338acf5283c512d9 | 38_11_9 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | t5-base model 23aa4f41cb7c08d4b05c8f327b22bfa0eb8c7ad9 10.1K 3 1 week ago main /home/wauplin/.cache/huggingface/hub/models--t5-base/snapshots/23aa4f41cb7c08d4b05c8f327b22bfa0eb8c7ad9
t5-small model 98ffebbb27340ec1b1abd7c45da12c253ee1882a 726.2M 6 1 week ago refs/pr/1 /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/98ffebbb27340ec1b1abd7c45da12c253ee1882a | 38_11_10 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | t5-small model d0a119eedb3718e34c648e594394474cf95e0617 485.8M 6 4 weeks ago /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/d0a119eedb3718e34c648e594394474cf95e0617
t5-small model d78aea13fa7ecd06c29e3e46195d6341255065d5 970.7M 9 1 week ago main /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/d78aea13fa7ecd06c29e3e46195d6341255065d5 | 38_11_11 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | Done in 0.0s. Scanned 6 repo(s) for a total of 3.4G.
Got 1 warning(s) while scanning. Use -vvv to print details.
``` | 38_11_12 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | Since the output is in tabular format, you can combine it with any `grep`-like tools to
filter the entries. Here is an example to filter only revisions from the "t5-small"
model on a Unix-based machine.
```text
➜ eval "huggingface-cli scan-cache -v" | grep "t5-small"
t5-small model 98ffebbb27340ec1b1abd7c45da12c253ee1882a 726.2M 6 1 week ago refs/pr/1 /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/98ffebbb27340ec1b1abd7c45da12c253ee1882a | 38_12_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | t5-small model d0a119eedb3718e34c648e594394474cf95e0617 485.8M 6 4 weeks ago /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/d0a119eedb3718e34c648e594394474cf95e0617
t5-small model d78aea13fa7ecd06c29e3e46195d6341255065d5 970.7M 9 1 week ago main /home/wauplin/.cache/huggingface/hub/models--t5-small/snapshots/d78aea13fa7ecd06c29e3e46195d6341255065d5
``` | 38_12_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | For a more advanced usage, use [`scan_cache_dir`] which is the python utility called by
the CLI tool.
You can use it to get a detailed report structured around 4 dataclasses:
- [`HFCacheInfo`]: complete report returned by [`scan_cache_dir`]
- [`CachedRepoInfo`]: information about a cached repo
- [`CachedRevisionInfo`]: information about a cached revision (e.g. "snapshot") inside a repo
- [`CachedFileInfo`]: information about a cached file in a snapshot | 38_13_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | - [`CachedFileInfo`]: information about a cached file in a snapshot
Here is a simple usage example. See reference for details.
```py
>>> from huggingface_hub import scan_cache_dir | 38_13_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | >>> hf_cache_info = scan_cache_dir()
HFCacheInfo(
size_on_disk=3398085269,
repos=frozenset({
CachedRepoInfo(
repo_id='t5-small',
repo_type='model',
repo_path=PosixPath(...),
size_on_disk=970726914,
nb_files=11,
last_accessed=1662971707.3567169,
last_modified=1662971107.3567169,
revisions=frozenset({
CachedRevisionInfo(
commit_hash='d78aea13fa7ecd06c29e3e46195d6341255065d5',
size_on_disk=970726339,
snapshot_path=PosixPath(...),
# No `last_accessed` as blobs are shared among revisions | 38_13_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | size_on_disk=970726339,
snapshot_path=PosixPath(...),
# No `last_accessed` as blobs are shared among revisions
last_modified=1662971107.3567169,
files=frozenset({
CachedFileInfo(
file_name='config.json',
size_on_disk=1197
file_path=PosixPath(...),
blob_path=PosixPath(...),
blob_last_accessed=1662971707.3567169,
blob_last_modified=1662971107.3567169,
),
CachedFileInfo(...),
...
}),
),
CachedRevisionInfo(...),
...
}),
),
CachedRepoInfo(...),
...
}),
warnings=[ | 38_13_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ),
CachedFileInfo(...),
...
}),
),
CachedRevisionInfo(...),
...
}),
),
CachedRepoInfo(...),
...
}),
warnings=[
CorruptedCacheException("Snapshots dir doesn't exist in cached repo: ..."),
CorruptedCacheException(...),
...
],
)
``` | 38_13_4 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | Scanning your cache is interesting but what you really want to do next is usually to
delete some portions to free up some space on your drive. This is possible using the
`delete-cache` CLI command. One can also programmatically use the
[`~HFCacheInfo.delete_revisions`] helper from [`HFCacheInfo`] object returned when
scanning the cache. | 38_14_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | To delete some cache, you need to pass a list of revisions to delete. The tool will
define a strategy to free up the space based on this list. It returns a
[`DeleteCacheStrategy`] object that describes which files and folders will be deleted.
The [`DeleteCacheStrategy`] allows give you how much space is expected to be freed.
Once you agree with the deletion, you must execute it to make the deletion effective. In
order to avoid discrepancies, you cannot edit a strategy object manually. | 38_15_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | order to avoid discrepancies, you cannot edit a strategy object manually.
The strategy to delete revisions is the following:
- the `snapshot` folder containing the revision symlinks is deleted.
- blobs files that are targeted only by revisions to be deleted are deleted as well.
- if a revision is linked to 1 or more `refs`, references are deleted.
- if all revisions from a repo are deleted, the entire cached repository is deleted.
<Tip> | 38_15_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | - if all revisions from a repo are deleted, the entire cached repository is deleted.
<Tip>
Revision hashes are unique across all repositories. This means you don't need to
provide any `repo_id` or `repo_type` when removing revisions.
</Tip>
<Tip warning={true}>
If a revision is not found in the cache, it will be silently ignored. Besides, if a file
or folder cannot be found while trying to delete it, a warning will be logged but no | 38_15_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | or folder cannot be found while trying to delete it, a warning will be logged but no
error is thrown. The deletion continues for other paths contained in the
[`DeleteCacheStrategy`] object.
</Tip> | 38_15_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | The easiest way to delete some revisions from your HF cache-system is to use the
`delete-cache` command from `huggingface-cli` tool. The command has two modes. By
default, a TUI (Terminal User Interface) is displayed to the user to select which
revisions to delete. This TUI is currently in beta as it has not been tested on all
platforms. If the TUI doesn't work on your machine, you can disable it using the
`--disable-tui` flag. | 38_16_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | This is the default mode. To use it, you first need to install extra dependencies by
running the following command:
```
pip install huggingface_hub["cli"]
```
Then run the command:
```
huggingface-cli delete-cache
```
You should now see a list of revisions that you can select/deselect:
<div class="flex justify-center">
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/delete-cache-tui.png"/>
</div>
Instructions: | 38_17_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | </div>
Instructions:
- Press keyboard arrow keys `<up>` and `<down>` to move the cursor.
- Press `<space>` to toggle (select/unselect) an item.
- When a revision is selected, the first line is updated to show you how much space
will be freed.
- Press `<enter>` to confirm your selection.
- If you want to cancel the operation and quit, you can select the first item
("None of the following"). If this item is selected, the delete process will be | 38_17_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | ("None of the following"). If this item is selected, the delete process will be
cancelled, no matter what other items are selected. Otherwise you can also press
`<ctrl+c>` to quit the TUI.
Once you've selected the revisions you want to delete and pressed `<enter>`, a last
confirmation message will be prompted. Press `<enter>` again and the deletion will be
effective. If you want to cancel, enter `n`.
```txt
✗ huggingface-cli delete-cache --dir ~/.cache/huggingface/hub | 38_17_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | effective. If you want to cancel, enter `n`.
```txt
✗ huggingface-cli delete-cache --dir ~/.cache/huggingface/hub
? Select revisions to delete: 2 revision(s) selected.
? 2 revisions selected counting for 3.1G. Confirm deletion ? Yes
Start deletion.
Done. Deleted 1 repo(s) and 0 revision(s) for a total of 3.1G.
``` | 38_17_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | As mentioned above, the TUI mode is currently in beta and is optional. It may be the
case that it doesn't work on your machine or that you don't find it convenient.
Another approach is to use the `--disable-tui` flag. The process is very similar as you
will be asked to manually review the list of revisions to delete. However, this manual
step will not take place in the terminal directly but in a temporary file generated on
the fly and that you can manually edit. | 38_18_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | the fly and that you can manually edit.
This file has all the instructions you need in the header. Open it in your favorite text
editor. To select/deselect a revision, simply comment/uncomment it with a `#`. Once the
manual review is done and the file is edited, you can save it. Go back to your terminal
and press `<enter>`. By default it will compute how much space would be freed with the
updated list of revisions. You can continue to edit the file or confirm with `"y"`.
```sh | 38_18_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | updated list of revisions. You can continue to edit the file or confirm with `"y"`.
```sh
huggingface-cli delete-cache --disable-tui
```
Example of command file:
```txt
# INSTRUCTIONS
# ------------
# This is a temporary file created by running `huggingface-cli delete-cache` with the
# `--disable-tui` option. It contains a set of revisions that can be deleted from your
# local cache directory.
#
# Please manually review the revisions you want to delete: | 38_18_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | # local cache directory.
#
# Please manually review the revisions you want to delete:
# - Revision hashes can be commented out with '#'.
# - Only non-commented revisions in this file will be deleted.
# - Revision hashes that are removed from this file are ignored as well.
# - If `CANCEL_DELETION` line is uncommented, the all cache deletion is cancelled and
# no changes will be applied.
#
# Once you've manually reviewed this file, please confirm deletion in the terminal. This | 38_18_3 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | # no changes will be applied.
#
# Once you've manually reviewed this file, please confirm deletion in the terminal. This
# file will be automatically removed once done.
# ------------ | 38_18_4 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | # KILL SWITCH
# ------------
# Un-comment following line to completely cancel the deletion process
# CANCEL_DELETION
# ------------
# REVISIONS
# ------------
# Dataset chrisjay/crowd-speech-africa (761.7M, used 5 days ago)
ebedcd8c55c90d39fd27126d29d8484566cd27ca # Refs: main # modified 5 days ago
# Dataset oscar (3.3M, used 4 days ago)
# 916f956518279c5e60c63902ebdf3ddf9fa9d629 # Refs: main # modified 4 days ago | 38_18_5 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | # Dataset oscar (3.3M, used 4 days ago)
# 916f956518279c5e60c63902ebdf3ddf9fa9d629 # Refs: main # modified 4 days ago
# Dataset wikiann (804.1K, used 2 weeks ago)
89d089624b6323d69dcd9e5eb2def0551887a73a # Refs: main # modified 2 weeks ago
# Dataset z-uo/male-LJSpeech-italian (5.5G, used 5 days ago)
# 9cfa5647b32c0a30d0adfca06bf198d82192a0d1 # Refs: main # modified 5 days ago
``` | 38_18_6 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | For more flexibility, you can also use the [`~HFCacheInfo.delete_revisions`] method
programmatically. Here is a simple example. See reference for details.
```py
>>> from huggingface_hub import scan_cache_dir
>>> delete_strategy = scan_cache_dir().delete_revisions(
... "81fd1d6e7847c99f5862c9fb81387956d99ec7aa"
... "e2983b237dccf3ab4937c97fa717319a9ca1a96d",
... "6c0e6080953db56375760c0471a8c5f2929baf11",
... )
>>> print("Will free " + delete_strategy.expected_freed_size_str)
Will free 8.6G | 38_19_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/guides/manage-cache.md | .md | >>> delete_strategy.execute()
Cache deletion done. Saved 8.6G.
``` | 38_19_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | <!--⚠️ Note that this file is in Markdown but contains specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
--> | 39_0_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | The `huggingface_hub` library is a library for interacting with the Hugging Face Hub, which is a
collection of git-based repositories (models, datasets or Spaces). There are two main
ways to access the Hub using `huggingface_hub`.
The first approach, the so-called "git-based" approach, is led by the [`Repository`] class.
This method uses a wrapper around the `git` command with additional functions specifically
designed to interact with the Hub. The second option, called the "HTTP-based" approach, | 39_1_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | designed to interact with the Hub. The second option, called the "HTTP-based" approach,
involves making HTTP requests using the [`HfApi`] client. Let's examine the pros and cons
of each approach. | 39_1_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | At first, `huggingface_hub` was mostly built around the [`Repository`] class. It provides
Python wrappers for common `git` commands such as `"git add"`, `"git commit"`, `"git push"`,
`"git tag"`, `"git checkout"`, etc.
The library also helps with setting credentials and tracking large files, which are often
used in machine learning repositories. Additionally, the library allows you to execute its
methods in the background, making it useful for uploading data during training. | 39_2_0 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | methods in the background, making it useful for uploading data during training.
The main advantage of using a [`Repository`] is that it allows you to maintain a local
copy of the entire repository on your machine. This can also be a disadvantage as
it requires you to constantly update and maintain this local copy. This is similar to
traditional software development where each developer maintains their own local copy and | 39_2_1 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | traditional software development where each developer maintains their own local copy and
pushes changes when working on a feature. However, in the context of machine learning,
this may not always be necessary as users may only need to download weights for inference
or convert weights from one format to another without the need to clone the entire
repository.
<Tip warning={true}> | 39_2_2 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/concepts/git_vs_http.md | .md | or convert weights from one format to another without the need to clone the entire
repository.
<Tip warning={true}>
[`Repository`] is now deprecated in favor of the http-based alternatives. Given its large adoption in legacy code, the complete removal of [`Repository`] will only happen in release `v1.0`.
</Tip> | 39_2_3 |