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/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_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.
--> | 200 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```python
Download a given file if it's not already present in the local cache. | 201 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | The new cache file layout looks like this:
- The cache directory contains one subfolder per repo_id (namespaced by repo type)
- inside each repo folder:
- refs is a list of the latest known revision => commit_hash pairs
- blobs contains the actual file blobs (identified by their git-sha or sha256, depending on
whether they're LFS files or not)
- snapshots contains one subfolder per commit, each "commit" contains the subset of the files | 202 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | whether they're LFS files or not)
- snapshots contains one subfolder per commit, each "commit" contains the subset of the files
that have been resolved at that particular commit. Each filename is a symlink to the blob
at that particular commit. | 203 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```
[ 96] .
└── [ 160] models--julien-c--EsperBERTo-small
├── [ 160] blobs
│ ├── [321M] 403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
│ ├── [ 398] 7cb18dc9bafbfcf74629a4b760af1b160957a83e
│ └── [1.4K] d7edf6bd2a681fb0175f7735299831ee1b22b812
├── [ 96] refs
│ └── [ 40] main
└── [ 128] snapshots
├── [ 128] 2439f60ef33a0d46d85da5001d52aeda5b00ce9f
│ ├── [ 52] README.md -> ../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812 | 204 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | │ ├── [ 52] README.md -> ../../blobs/d7edf6bd2a681fb0175f7735299831ee1b22b812
│ └── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
└── [ 128] bbc77c8132af1cc5cf678da3f1ddf2de43606d48
├── [ 52] README.md -> ../../blobs/7cb18dc9bafbfcf74629a4b760af1b160957a83e
└── [ 76] pytorch_model.bin -> ../../blobs/403450e234d65943a7dcf7e05a771ce3c92faa84dd07db4ac20f592037a1e4bd
``` | 205 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
cache-system, it's optimized for regularly pulling the latest version of a repository. | 206 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Args:
repo_id (`str`):
A user or an organization name and a repo name separated by a `/`.
filename (`str`):
The name of the file in the repo.
subfolder (`str`, *optional*):
An optional value corresponding to a folder inside the model repo.
repo_type (`str`, *optional*):
Set to `"dataset"` or `"space"` if downloading from a dataset or space,
`None` or `"model"` if downloading from a model. Default is `None`.
revision (`str`, *optional*):
An optional Git revision id which can be a branch name, a tag, or a | 207 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | revision (`str`, *optional*):
An optional Git revision id which can be a branch name, a tag, or a
commit hash.
library_name (`str`, *optional*):
The name of the library to which the object corresponds.
library_version (`str`, *optional*):
The version of the library.
cache_dir (`str`, `Path`, *optional*):
Path to the folder where cached files are stored.
local_dir (`str` or `Path`, *optional*):
If provided, the downloaded file will be placed under this directory.
user_agent (`dict`, `str`, *optional*): | 208 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | If provided, the downloaded file will be placed under this directory.
user_agent (`dict`, `str`, *optional*):
The user-agent info in the form of a dictionary or a string.
force_download (`bool`, *optional*, defaults to `False`):
Whether the file should be downloaded even if it already exists in
the local cache.
proxies (`dict`, *optional*):
Dictionary mapping protocol to the URL of the proxy passed to
`requests.request`.
etag_timeout (`float`, *optional*, defaults to `10`): | 209 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | `requests.request`.
etag_timeout (`float`, *optional*, defaults to `10`):
When fetching ETag, how many seconds to wait for the server to send
data before giving up which is passed to `requests.request`.
token (`str`, `bool`, *optional*):
A token to be used for the download.
- If `True`, the token is read from the HuggingFace config
folder.
- If a string, it's used as the authentication token.
local_files_only (`bool`, *optional*, defaults to `False`): | 210 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | folder.
- If a string, it's used as the authentication token.
local_files_only (`bool`, *optional*, defaults to `False`):
If `True`, avoid downloading the file and return the path to the
local cached file if it exists.
headers (`dict`, *optional*):
Additional headers to be sent with the request. | 211 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Returns:
`str`: Local path of file or if networking is off, last version of file cached on disk. | 212 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Raises:
[`~utils.RepositoryNotFoundError`]
If the repository to download from cannot be found. This may be because it doesn't exist,
or because it is set to `private` and you do not have access.
[`~utils.RevisionNotFoundError`]
If the revision to download from cannot be found.
[`~utils.EntryNotFoundError`]
If the file to download cannot be found.
[`~utils.LocalEntryNotFoundError`]
If network is disabled or unavailable and file is not found in cache. | 213 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | [`~utils.LocalEntryNotFoundError`]
If network is disabled or unavailable and file is not found in cache.
[`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
If `token=True` but the token cannot be found.
[`OSError`](https://docs.python.org/3/library/exceptions.html#OSError)
If ETag cannot be determined.
[`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
If some parameter value is invalid.
``` | 214 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```python
Construct the URL of a file from the given information.
The resolved address can either be a huggingface.co-hosted url, or a link to
Cloudfront (a Content Delivery Network, or CDN) for large files which are
more than a few MBs. | 215 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Args:
repo_id (`str`):
A namespace (user or an organization) name and a repo name separated
by a `/`.
filename (`str`):
The name of the file in the repo.
subfolder (`str`, *optional*):
An optional value corresponding to a folder inside the repo.
repo_type (`str`, *optional*):
Set to `"dataset"` or `"space"` if downloading from a dataset or space,
`None` or `"model"` if downloading from a model. Default is `None`.
revision (`str`, *optional*): | 216 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | `None` or `"model"` if downloading from a model. Default is `None`.
revision (`str`, *optional*):
An optional Git revision id which can be a branch name, a tag, or a
commit hash. | 217 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Example:
```python
>>> from huggingface_hub import hf_hub_url
>>> hf_hub_url(
... repo_id="julien-c/EsperBERTo-small", filename="pytorch_model.bin"
... )
'https://huggingface.co/julien-c/EsperBERTo-small/resolve/main/pytorch_model.bin'
```
<Tip>
Notes:
Cloudfront is replicated over the globe so downloads are way faster for
the end user (and it also lowers our bandwidth costs). | 218 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Cloudfront is replicated over the globe so downloads are way faster for
the end user (and it also lowers our bandwidth costs).
Cloudfront aggressively caches files by default (default TTL is 24
hours), however this is not an issue here because we implement a
git-based versioning system on huggingface.co, which means that we store
the files on S3/Cloudfront in a content-addressable way (i.e., the file
name is its hash). Using content-addressable filenames means cache can't
ever be stale. | 219 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | In terms of client-side caching from this library, we base our caching
on the objects' entity tag (`ETag`), which is an identifier of a
specific version of a resource [1]_. An object's ETag is: its git-sha1
if stored in git, or its sha256 if stored in git-lfs.
</Tip>
References:
- [1] https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/ETag
``` | 220 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```python
Download repo files.
Download a whole snapshot of a repo's files at the specified revision. This is useful when you want all files from
a repo, because you don't know which ones you will need a priori. All files are nested inside a folder in order
to keep their actual filename relative to that folder. You can also filter which files to download using
`allow_patterns` and `ignore_patterns`. | 221 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
cache-system, it's optimized for regularly pulling the latest version of a repository. | 222 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | An alternative would be to clone the repo but this requires git and git-lfs to be installed and properly
configured. It is also not possible to filter which files to download when cloning a repository using git. | 223 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Args:
repo_id (`str`):
A user or an organization name and a repo name separated by a `/`.
repo_type (`str`, *optional*):
Set to `"dataset"` or `"space"` if downloading from a dataset or space,
`None` or `"model"` if downloading from a model. Default is `None`.
revision (`str`, *optional*):
An optional Git revision id which can be a branch name, a tag, or a
commit hash.
cache_dir (`str`, `Path`, *optional*):
Path to the folder where cached files are stored.
local_dir (`str` or `Path`, *optional*): | 224 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Path to the folder where cached files are stored.
local_dir (`str` or `Path`, *optional*):
If provided, the downloaded files will be placed under this directory.
library_name (`str`, *optional*):
The name of the library to which the object corresponds.
library_version (`str`, *optional*):
The version of the library.
user_agent (`str`, `dict`, *optional*):
The user-agent info in the form of a dictionary or a string.
proxies (`dict`, *optional*):
Dictionary mapping protocol to the URL of the proxy passed to | 225 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | proxies (`dict`, *optional*):
Dictionary mapping protocol to the URL of the proxy passed to
`requests.request`.
etag_timeout (`float`, *optional*, defaults to `10`):
When fetching ETag, how many seconds to wait for the server to send
data before giving up which is passed to `requests.request`.
force_download (`bool`, *optional*, defaults to `False`):
Whether the file should be downloaded even if it already exists in the local cache.
token (`str`, `bool`, *optional*):
A token to be used for the download. | 226 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | token (`str`, `bool`, *optional*):
A token to be used for the download.
- If `True`, the token is read from the HuggingFace config
folder.
- If a string, it's used as the authentication token.
headers (`dict`, *optional*):
Additional headers to include in the request. Those headers take precedence over the others.
local_files_only (`bool`, *optional*, defaults to `False`):
If `True`, avoid downloading the file and return the path to the
local cached file if it exists. | 227 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | If `True`, avoid downloading the file and return the path to the
local cached file if it exists.
allow_patterns (`List[str]` or `str`, *optional*):
If provided, only files matching at least one pattern are downloaded.
ignore_patterns (`List[str]` or `str`, *optional*):
If provided, files matching any of the patterns are not downloaded.
max_workers (`int`, *optional*):
Number of concurrent threads to download files (1 thread = 1 file download).
Defaults to 8.
tqdm_class (`tqdm`, *optional*): | 228 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Number of concurrent threads to download files (1 thread = 1 file download).
Defaults to 8.
tqdm_class (`tqdm`, *optional*):
If provided, overwrites the default behavior for the progress bar. Passed
argument must inherit from `tqdm.auto.tqdm` or at least mimic its behavior.
Note that the `tqdm_class` is not passed to each individual download.
Defaults to the custom HF progress bar that can be disabled by setting
`HF_HUB_DISABLE_PROGRESS_BARS` environment variable. | 229 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Returns:
`str`: folder path of the repo snapshot. | 230 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Raises:
[`~utils.RepositoryNotFoundError`]
If the repository to download from cannot be found. This may be because it doesn't exist,
or because it is set to `private` and you do not have access.
[`~utils.RevisionNotFoundError`]
If the revision to download from cannot be found.
[`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
If `token=True` and the token cannot be found.
[`OSError`](https://docs.python.org/3/library/exceptions.html#OSError) if | 231 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | If `token=True` and the token cannot be found.
[`OSError`](https://docs.python.org/3/library/exceptions.html#OSError) if
ETag cannot be determined.
[`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
if some parameter value is invalid.
``` | 232 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```python
Fetch metadata of a file versioned on the Hub for a given url. | 233 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Args:
url (`str`):
File url, for example returned by [`hf_hub_url`].
token (`str` or `bool`, *optional*):
A token to be used for the download.
- If `True`, the token is read from the HuggingFace config
folder.
- If `False` or `None`, no token is provided.
- If a string, it's used as the authentication token.
proxies (`dict`, *optional*):
Dictionary mapping protocol to the URL of the proxy passed to
`requests.request`.
timeout (`float`, *optional*, defaults to 10): | 234 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | `requests.request`.
timeout (`float`, *optional*, defaults to 10):
How many seconds to wait for the server to send metadata before giving up.
library_name (`str`, *optional*):
The name of the library to which the object corresponds.
library_version (`str`, *optional*):
The version of the library.
user_agent (`dict`, `str`, *optional*):
The user-agent info in the form of a dictionary or a string.
headers (`dict`, *optional*):
Additional headers to be sent with the request. | 235 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | Returns:
A [`HfFileMetadata`] object containing metadata such as location, etag, size and
commit_hash.
``` | 236 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | ```python
Data structure containing information about a file versioned on the Hub.
Returned by [`get_hf_file_metadata`] based on a URL.
Args:
commit_hash (`str`, *optional*):
The commit_hash related to the file.
etag (`str`, *optional*):
Etag of the file on the server.
location (`str`):
Location where to download the file. Can be a Hub url or not (CDN).
size (`size`):
Size of the file. In case of an LFS file, contains the size of the actual
LFS file, not the pointer.
``` | 237 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/file_download.md | .md | The methods displayed above are designed to work with a caching system that prevents
re-downloading files. The caching system was updated in v0.8.0 to become the central
cache-system shared across libraries that depend on the Hub.
Read the [cache-system guide](../guides/manage-cache) for a detailed presentation of caching at
at HF. | 238 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.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.
--> | 239 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | `huggingface_hub` provides helpers to save and load ML model weights in a standardized way. This part of the library is still under development and will be improved in future releases. The goal is to harmonize how weights are saved and loaded across the Hub, both to remove code duplication across libraries and to establish consistent conventions. | 240 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | DDUF is a file format designed for diffusion models. It allows saving all the information to run a model in a single file. This work is inspired by the [GGUF](https://github.com/ggerganov/ggml/blob/master/docs/gguf.md) format. `huggingface_hub` provides helpers to save and load DDUF files, ensuring the file format is respected.
<Tip warning={true}>
This is a very early version of the parser. The API and implementation can evolve in the near future. | 241 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | <Tip warning={true}>
This is a very early version of the parser. The API and implementation can evolve in the near future.
The parser currently does very little validation. For more details about the file format, check out https://github.com/huggingface/huggingface.js/tree/main/packages/dduf.
</Tip> | 242 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Here is how to export a folder containing different parts of a diffusion model using [`export_folder_as_dduf`]:
```python
# Export a folder as a DDUF file
>>> from huggingface_hub import export_folder_as_dduf
>>> export_folder_as_dduf("FLUX.1-dev.dduf", folder_path="path/to/FLUX.1-dev")
```
For more flexibility, you can use [`export_entries_as_dduf`] and pass a list of files to include in the final DDUF file:
```python
# Export specific files from the local disk. | 243 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
# Export specific files from the local disk.
>>> from huggingface_hub import export_entries_as_dduf
>>> export_entries_as_dduf(
... dduf_path="stable-diffusion-v1-4-FP16.dduf",
... entries=[ # List entries to add to the DDUF file (here, only FP16 weights)
... ("model_index.json", "path/to/model_index.json"),
... ("vae/config.json", "path/to/vae/config.json"), | 244 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... ("model_index.json", "path/to/model_index.json"),
... ("vae/config.json", "path/to/vae/config.json"),
... ("vae/diffusion_pytorch_model.fp16.safetensors", "path/to/vae/diffusion_pytorch_model.fp16.safetensors"),
... ("text_encoder/config.json", "path/to/text_encoder/config.json"),
... ("text_encoder/model.fp16.safetensors", "path/to/text_encoder/model.fp16.safetensors"),
... # ... add more entries here
... ]
... )
``` | 245 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... # ... add more entries here
... ]
... )
```
The `entries` parameter also supports passing an iterable of paths or bytes. This can prove useful if you have a loaded model and want to serialize it directly into a DDUF file instead of having to serialize each component to disk first and then as a DDUF file. Here is an example of how a `StableDiffusionPipeline` can be serialized as DDUF:
```python
# Export state_dicts one by one from a loaded pipeline | 246 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
# Export state_dicts one by one from a loaded pipeline
>>> from diffusers import DiffusionPipeline
>>> from typing import Generator, Tuple
>>> import safetensors.torch
>>> from huggingface_hub import export_entries_as_dduf
>>> pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
... # ... do some work with the pipeline | 247 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> def as_entries(pipe: DiffusionPipeline) -> Generator[Tuple[str, bytes], None, None]:
... # Build a generator that yields the entries to add to the DDUF file.
... # The first element of the tuple is the filename in the DDUF archive (must use UNIX separator!). The second element is the content of the file.
... # Entries will be evaluated lazily when the DDUF file is created (only 1 entry is loaded in memory at a time)
... yield "vae/config.json", pipe.vae.to_json_string().encode() | 248 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... yield "vae/config.json", pipe.vae.to_json_string().encode()
... yield "vae/diffusion_pytorch_model.safetensors", safetensors.torch.save(pipe.vae.state_dict())
... yield "text_encoder/config.json", pipe.text_encoder.config.to_json_string().encode()
... yield "text_encoder/model.safetensors", safetensors.torch.save(pipe.text_encoder.state_dict())
... # ... add more entries here | 249 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> export_entries_as_dduf(dduf_path="stable-diffusion-v1-4.dduf", entries=as_entries(pipe))
```
**Note:** in practice, `diffusers` provides a method to directly serialize a pipeline in a DDUF file. The snippet above is only meant as an example. | 250 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
>>> import json
>>> import safetensors.torch
>>> from huggingface_hub import read_dduf_file
# Read DDUF metadata
>>> dduf_entries = read_dduf_file("FLUX.1-dev.dduf")
# Returns a mapping filename <> DDUFEntry
>>> dduf_entries["model_index.json"]
DDUFEntry(filename='model_index.json', offset=66, length=587) | 251 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | # Load model index as JSON
>>> json.loads(dduf_entries["model_index.json"].read_text()) | 252 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | {'_class_name': 'FluxPipeline', '_diffusers_version': '0.32.0.dev0', '_name_or_path': 'black-forest-labs/FLUX.1-dev', 'scheduler': ['diffusers', 'FlowMatchEulerDiscreteScheduler'], 'text_encoder': ['transformers', 'CLIPTextModel'], 'text_encoder_2': ['transformers', 'T5EncoderModel'], 'tokenizer': ['transformers', 'CLIPTokenizer'], 'tokenizer_2': ['transformers', 'T5TokenizerFast'], 'transformer': ['diffusers', 'FluxTransformer2DModel'], 'vae': ['diffusers', 'AutoencoderKL']} | 253 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | # Load VAE weights using safetensors
>>> with dduf_entries["vae/diffusion_pytorch_model.safetensors"].as_mmap() as mm:
... state_dict = safetensors.torch.load(mm)
``` | 254 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Write a DDUF file from an iterable of entries.
This is a lower-level helper than [`export_folder_as_dduf`] that allows more flexibility when serializing data.
In particular, you don't need to save the data on disk before exporting it in the DDUF file. | 255 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Args:
dduf_path (`str` or `os.PathLike`):
The path to the DDUF file to write.
entries (`Iterable[Tuple[str, Union[str, Path, bytes]]]`):
An iterable of entries to write in the DDUF file. Each entry is a tuple with the filename and the content.
The filename should be the path to the file in the DDUF archive.
The content can be a string or a pathlib.Path representing a path to a file on the local disk or directly the content as bytes. | 256 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Raises:
- [`DDUFExportError`]: If anything goes wrong during the export (e.g. invalid entry name, missing 'model_index.json', etc.).
Example:
```python | 257 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> from huggingface_hub import export_entries_as_dduf
>>> export_entries_as_dduf(
... dduf_path="stable-diffusion-v1-4-FP16.dduf",
... entries=[ # List entries to add to the DDUF file (here, only FP16 weights)
... ("model_index.json", "path/to/model_index.json"),
... ("vae/config.json", "path/to/vae/config.json"),
... ("vae/diffusion_pytorch_model.fp16.safetensors", "path/to/vae/diffusion_pytorch_model.fp16.safetensors"), | 258 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... ("vae/diffusion_pytorch_model.fp16.safetensors", "path/to/vae/diffusion_pytorch_model.fp16.safetensors"),
... ("text_encoder/config.json", "path/to/text_encoder/config.json"),
... ("text_encoder/model.fp16.safetensors", "path/to/text_encoder/model.fp16.safetensors"),
... # ... add more entries here
... ]
... )
``` | 259 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python | 260 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> from diffusers import DiffusionPipeline
>>> from typing import Generator, Tuple
>>> import safetensors.torch
>>> from huggingface_hub import export_entries_as_dduf
>>> pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
... # ... do some work with the pipeline
>>> def as_entries(pipe: DiffusionPipeline) -> Generator[Tuple[str, bytes], None, None]:
... # Build an generator that yields the entries to add to the DDUF file. | 261 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... # Build an generator that yields the entries to add to the DDUF file.
... # The first element of the tuple is the filename in the DDUF archive (must use UNIX separator!). The second element is the content of the file.
... # Entries will be evaluated lazily when the DDUF file is created (only 1 entry is loaded in memory at a time)
... yield "vae/config.json", pipe.vae.to_json_string().encode() | 262 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ... yield "vae/config.json", pipe.vae.to_json_string().encode()
... yield "vae/diffusion_pytorch_model.safetensors", safetensors.torch.save(pipe.vae.state_dict())
... yield "text_encoder/config.json", pipe.text_encoder.config.to_json_string().encode()
... yield "text_encoder/model.safetensors", safetensors.torch.save(pipe.text_encoder.state_dict())
... # ... add more entries here
>>> export_entries_as_dduf(dduf_path="stable-diffusion-v1-4.dduf", entries=as_entries(pipe))
```
``` | 263 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Export a folder as a DDUF file.
AUses [`export_entries_as_dduf`] under the hood.
Args:
dduf_path (`str` or `os.PathLike`):
The path to the DDUF file to write.
folder_path (`str` or `os.PathLike`):
The path to the folder containing the diffusion model.
Example:
```python
>>> from huggingface_hub import export_folder_as_dduf
>>> export_folder_as_dduf(dduf_path="FLUX.1-dev.dduf", folder_path="path/to/FLUX.1-dev")
```
``` | 264 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Read a DDUF file and return a dictionary of entries.
Only the metadata is read, the data is not loaded in memory.
Args:
dduf_path (`str` or `os.PathLike`):
The path to the DDUF file to read.
Returns:
`Dict[str, DDUFEntry]`:
A dictionary of [`DDUFEntry`] indexed by filename.
Raises:
- [`DDUFCorruptedFileError`]: If the DDUF file is corrupted (i.e. doesn't follow the DDUF format).
Example:
```python
>>> import json
>>> import safetensors.torch
>>> from huggingface_hub import read_dduf_file | 265 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> dduf_entries = read_dduf_file("FLUX.1-dev.dduf") | 266 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> dduf_entries["model_index.json"]
DDUFEntry(filename='model_index.json', offset=66, length=587) | 267 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> json.loads(dduf_entries["model_index.json"].read_text())
{'_class_name': 'FluxPipeline', '_diffusers_version': '0.32.0.dev0', '_name_or_path': 'black-forest-labs/FLUX.1-dev', ... | 268 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> with dduf_entries["vae/diffusion_pytorch_model.safetensors"].as_mmap() as mm:
... state_dict = safetensors.torch.load(mm)
```
``` | 269 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Object representing a file entry in a DDUF file.
See [`read_dduf_file`] for how to read a DDUF file.
Attributes:
filename (str):
The name of the file in the DDUF archive.
offset (int):
The offset of the file in the DDUF archive.
length (int):
The length of the file in the DDUF archive.
dduf_path (str):
The path to the DDUF archive (for internal use).
``` | 270 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Base exception for errors related to the DDUF format.
``` | 271 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Exception thrown when the DDUF file is corrupted.
``` | 272 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Base exception for errors during DDUF export.
``` | 273 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Exception thrown when the entry name is invalid.
``` | 274 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | The main helper of the `serialization` module takes a torch `nn.Module` as input and saves it to disk. It handles the logic to save shared tensors (see [safetensors explanation](https://huggingface.co/docs/safetensors/torch_shared_tensors)) as well as logic to split the state dictionary into shards, using [`split_torch_state_dict_into_shards`] under the hood. At the moment, only `torch` framework is supported. | 275 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | If you want to save a state dictionary (e.g. a mapping between layer names and related tensors) instead of a `nn.Module`, you can use [`save_torch_state_dict`] which provides the same features. This is useful for example if you want to apply custom logic to the state dict before saving it. | 276 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Saves a given torch model to disk, handling sharding and shared tensors issues.
See also [`save_torch_state_dict`] to save a state dict with more flexibility.
For more information about tensor sharing, check out [this guide](https://huggingface.co/docs/safetensors/torch_shared_tensors). | 277 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | The model state dictionary is split into shards so that each shard is smaller than a given size. The shards are
saved in the `save_directory` with the given `filename_pattern`. If the model is too big to fit in a single shard,
an index file is saved in the `save_directory` to indicate where each tensor is saved. This helper uses
[`split_torch_state_dict_into_shards`] under the hood. If `safe_serialization` is `True`, the shards are saved as | 278 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | [`split_torch_state_dict_into_shards`] under the hood. If `safe_serialization` is `True`, the shards are saved as
safetensors (the default). Otherwise, the shards are saved as pickle. | 279 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Before saving the model, the `save_directory` is cleaned from any previous shard files.
<Tip warning={true}>
If one of the model's tensor is bigger than `max_shard_size`, it will end up in its own shard which will have a
size greater than `max_shard_size`.
</Tip>
<Tip warning={true}> | 280 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | </Tip>
<Tip warning={true}>
If your model is a `transformers.PreTrainedModel`, you should pass `model._tied_weights_keys` as `shared_tensors_to_discard` to properly handle shared tensors saving. This ensures the correct duplicate tensors are discarded during saving.
</Tip> | 281 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Args:
model (`torch.nn.Module`):
The model to save on disk.
save_directory (`str` or `Path`):
The directory in which the model will be saved.
filename_pattern (`str`, *optional*):
The pattern to generate the files names in which the model will be saved. Pattern must be a string that
can be formatted with `filename_pattern.format(suffix=...)` and must contain the keyword `suffix`
Defaults to `"model{suffix}.safetensors"` or `pytorch_model{suffix}.bin` depending on `safe_serialization`
parameter. | 282 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Defaults to `"model{suffix}.safetensors"` or `pytorch_model{suffix}.bin` depending on `safe_serialization`
parameter.
force_contiguous (`boolean`, *optional*):
Forcing the state_dict to be saved as contiguous tensors. This has no effect on the correctness of the
model, but it could potentially change performance if the layout of the tensor was chosen specifically for
that reason. Defaults to `True`.
max_shard_size (`int` or `str`, *optional*):
The maximum size of each shard, in bytes. Defaults to 5GB. | 283 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | max_shard_size (`int` or `str`, *optional*):
The maximum size of each shard, in bytes. Defaults to 5GB.
metadata (`Dict[str, str]`, *optional*):
Extra information to save along with the model. Some metadata will be added for each dropped tensors.
This information will not be enough to recover the entire shared structure but might help understanding
things.
safe_serialization (`bool`, *optional*):
Whether to save as safetensors, which is the default behavior. If `False`, the shards are saved as pickle. | 284 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Whether to save as safetensors, which is the default behavior. If `False`, the shards are saved as pickle.
Safe serialization is recommended for security reasons. Saving as pickle is deprecated and will be removed
in a future version.
is_main_process (`bool`, *optional*):
Whether the process calling this is the main process or not. Useful when in distributed training like
TPUs and need to call this function from all processes. In this case, set `is_main_process=True` only on | 285 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | TPUs and need to call this function from all processes. In this case, set `is_main_process=True` only on
the main process to avoid race conditions. Defaults to True.
shared_tensors_to_discard (`List[str]`, *optional*):
List of tensor names to drop when saving shared tensors. If not provided and shared tensors are
detected, it will drop the first name alphabetically. | 286 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Example:
```py
>>> from huggingface_hub import save_torch_model
>>> model = ... # A PyTorch model | 287 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> save_torch_model(model, "path/to/folder") | 288 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | >>> from huggingface_hub import load_torch_model # TODO
>>> load_torch_model(model, "path/to/folder")
>>>
```
``` | 289 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | ```python
Save a model state dictionary to the disk, handling sharding and shared tensors issues.
See also [`save_torch_model`] to directly save a PyTorch model.
For more information about tensor sharing, check out [this guide](https://huggingface.co/docs/safetensors/torch_shared_tensors). | 290 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | The model state dictionary is split into shards so that each shard is smaller than a given size. The shards are
saved in the `save_directory` with the given `filename_pattern`. If the model is too big to fit in a single shard,
an index file is saved in the `save_directory` to indicate where each tensor is saved. This helper uses
[`split_torch_state_dict_into_shards`] under the hood. If `safe_serialization` is `True`, the shards are saved as | 291 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | [`split_torch_state_dict_into_shards`] under the hood. If `safe_serialization` is `True`, the shards are saved as
safetensors (the default). Otherwise, the shards are saved as pickle. | 292 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Before saving the model, the `save_directory` is cleaned from any previous shard files.
<Tip warning={true}>
If one of the model's tensor is bigger than `max_shard_size`, it will end up in its own shard which will have a
size greater than `max_shard_size`.
</Tip>
<Tip warning={true}> | 293 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | </Tip>
<Tip warning={true}>
If your model is a `transformers.PreTrainedModel`, you should pass `model._tied_weights_keys` as `shared_tensors_to_discard` to properly handle shared tensors saving. This ensures the correct duplicate tensors are discarded during saving.
</Tip> | 294 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Args:
state_dict (`Dict[str, torch.Tensor]`):
The state dictionary to save.
save_directory (`str` or `Path`):
The directory in which the model will be saved.
filename_pattern (`str`, *optional*):
The pattern to generate the files names in which the model will be saved. Pattern must be a string that
can be formatted with `filename_pattern.format(suffix=...)` and must contain the keyword `suffix`
Defaults to `"model{suffix}.safetensors"` or `pytorch_model{suffix}.bin` depending on `safe_serialization` | 295 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Defaults to `"model{suffix}.safetensors"` or `pytorch_model{suffix}.bin` depending on `safe_serialization`
parameter.
force_contiguous (`boolean`, *optional*):
Forcing the state_dict to be saved as contiguous tensors. This has no effect on the correctness of the
model, but it could potentially change performance if the layout of the tensor was chosen specifically for
that reason. Defaults to `True`.
max_shard_size (`int` or `str`, *optional*):
The maximum size of each shard, in bytes. Defaults to 5GB. | 296 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | max_shard_size (`int` or `str`, *optional*):
The maximum size of each shard, in bytes. Defaults to 5GB.
metadata (`Dict[str, str]`, *optional*):
Extra information to save along with the model. Some metadata will be added for each dropped tensors.
This information will not be enough to recover the entire shared structure but might help understanding
things.
safe_serialization (`bool`, *optional*):
Whether to save as safetensors, which is the default behavior. If `False`, the shards are saved as pickle. | 297 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | Whether to save as safetensors, which is the default behavior. If `False`, the shards are saved as pickle.
Safe serialization is recommended for security reasons. Saving as pickle is deprecated and will be removed
in a future version.
is_main_process (`bool`, *optional*):
Whether the process calling this is the main process or not. Useful when in distributed training like
TPUs and need to call this function from all processes. In this case, set `is_main_process=True` only on | 298 |
/Users/nielsrogge/Documents/python_projecten/huggingface_hub/docs/source/en/package_reference/serialization.md | .md | TPUs and need to call this function from all processes. In this case, set `is_main_process=True` only on
the main process to avoid race conditions. Defaults to True.
shared_tensors_to_discard (`List[str]`, *optional*):
List of tensor names to drop when saving shared tensors. If not provided and shared tensors are
detected, it will drop the first name alphabetically. | 299 |