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feat: deploy Gemma 4 to hf space
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# Copyright 2026 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Contains commands to interact with datasets on the Hugging Face Hub.
Usage:
# list datasets on the Hub
hf datasets ls
# list datasets with a search query
hf datasets ls --search "code"
# get info about a dataset
hf datasets info HuggingFaceFW/fineweb
"""
import enum
from typing import Annotated, get_args
import typer
from huggingface_hub._dataset_viewer import execute_raw_sql_query
from huggingface_hub.errors import CLIError, RepositoryNotFoundError, RevisionNotFoundError
from huggingface_hub.hf_api import DatasetSort_T, ExpandDatasetProperty_T
from ._cli_utils import (
AuthorOpt,
FilterOpt,
FormatWithAutoOpt,
LimitOpt,
RevisionOpt,
SearchOpt,
TokenOpt,
api_object_to_dict,
get_hf_api,
make_expand_properties_parser,
typer_factory,
)
from ._output import OutputFormatWithAuto, out
_EXPAND_PROPERTIES = sorted(get_args(ExpandDatasetProperty_T))
_SORT_OPTIONS = get_args(DatasetSort_T)
DatasetSortEnum = enum.Enum("DatasetSortEnum", {s: s for s in _SORT_OPTIONS}, type=str) # type: ignore[misc]
ExpandOpt = Annotated[
str | None,
typer.Option(
help=f"Comma-separated properties to return. When used, only the listed properties (and id) are returned. Example: '--expand=downloads,likes,tags'. Valid: {', '.join(_EXPAND_PROPERTIES)}.",
callback=make_expand_properties_parser(_EXPAND_PROPERTIES),
),
]
datasets_cli = typer_factory(help="Interact with datasets on the Hub.")
@datasets_cli.command(
"list | ls",
examples=[
"hf datasets ls",
"hf datasets ls --sort downloads --limit 10",
'hf datasets ls --search "code"',
],
)
def datasets_ls(
search: SearchOpt = None,
author: AuthorOpt = None,
filter: FilterOpt = None,
sort: Annotated[
DatasetSortEnum | None,
typer.Option(help="Sort results."),
] = None,
limit: LimitOpt = 10,
expand: ExpandOpt = None,
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""List datasets on the Hub."""
api = get_hf_api(token=token)
sort_key = sort.value if sort else None
results = [
api_object_to_dict(dataset_info)
for dataset_info in api.list_datasets(
filter=filter,
author=author,
search=search,
sort=sort_key,
limit=limit,
expand=expand, # type: ignore
)
]
out.table(results)
@datasets_cli.command(
"info",
examples=[
"hf datasets info HuggingFaceFW/fineweb",
"hf datasets info my-dataset --expand downloads,likes,tags",
],
)
def datasets_info(
dataset_id: Annotated[str, typer.Argument(help="The dataset ID (e.g. `username/repo-name`).")],
revision: RevisionOpt = None,
expand: ExpandOpt = None,
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""Get info about a dataset on the Hub."""
api = get_hf_api(token=token)
try:
info = api.dataset_info(repo_id=dataset_id, revision=revision, expand=expand) # type: ignore
except RepositoryNotFoundError as e:
raise CLIError(f"Dataset '{dataset_id}' not found.") from e
except RevisionNotFoundError as e:
raise CLIError(f"Revision '{revision}' not found on '{dataset_id}'.") from e
out.dict(info)
@datasets_cli.command(
"parquet",
examples=[
"hf datasets parquet cfahlgren1/hub-stats",
"hf datasets parquet cfahlgren1/hub-stats --subset models",
"hf datasets parquet cfahlgren1/hub-stats --split train",
"hf datasets parquet cfahlgren1/hub-stats --format json",
],
)
def datasets_parquet(
dataset_id: Annotated[str, typer.Argument(help="The dataset ID (e.g. `username/repo-name`).")],
subset: Annotated[str | None, typer.Option("--subset", help="Filter parquet entries by subset/config.")] = None,
split: Annotated[str | None, typer.Option(help="Filter parquet entries by split.")] = None,
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""List parquet file URLs available for a dataset."""
api = get_hf_api(token=token)
entries = api.list_dataset_parquet_files(repo_id=dataset_id, config=subset)
filtered = [entry for entry in entries if split is None or entry.split == split]
results = [
{"subset": entry.config, "split": entry.split, "url": entry.url, "size": entry.size} for entry in filtered
]
out.table(results, headers=["subset", "split", "url", "size"], id_key="url")
@datasets_cli.command(
"sql",
examples=[
"hf datasets sql \"SELECT COUNT(*) AS rows FROM read_parquet('https://huggingface.co/api/datasets/cfahlgren1/hub-stats/parquet/models/train/0.parquet')\"",
"hf datasets sql \"SELECT * FROM read_parquet('https://huggingface.co/api/datasets/cfahlgren1/hub-stats/parquet/models/train/0.parquet') LIMIT 5\" --format json",
],
)
def datasets_sql(
sql: Annotated[str, typer.Argument(help="Raw SQL query to execute.")],
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""Execute a raw SQL query with DuckDB against dataset parquet URLs."""
try:
result = execute_raw_sql_query(sql_query=sql, token=token)
except ImportError as e:
raise CLIError(str(e)) from e
out.table(result)