GGSheng's picture
feat: deploy Gemma 4 to hf space
08c964e verified
# 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 models on the Hugging Face Hub.
Usage:
# list models on the Hub
hf models ls
# list models with a search query
hf models ls --search "llama"
# get info about a model
hf models info Lightricks/LTX-2
"""
import enum
from typing import Annotated, get_args
import typer
from huggingface_hub.errors import CLIError, RepositoryNotFoundError, RevisionNotFoundError
from huggingface_hub.hf_api import ExpandModelProperty_T, ModelSort_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(ExpandModelProperty_T))
_SORT_OPTIONS = get_args(ModelSort_T)
ModelSortEnum = enum.Enum("ModelSortEnum", {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),
),
]
models_cli = typer_factory(help="Interact with models on the Hub.")
@models_cli.command(
"list | ls",
examples=[
"hf models ls --sort downloads --limit 10",
'hf models ls --search "llama" --author meta-llama',
"hf models ls --num-parameters min:6B,max:128B --sort likes",
],
)
def models_ls(
search: SearchOpt = None,
author: AuthorOpt = None,
filter: FilterOpt = None,
num_parameters: Annotated[
str | None,
typer.Option(help="Filter by parameter count, e.g. 'min:6B,max:128B'."),
] = None,
sort: Annotated[
ModelSortEnum | None,
typer.Option(help="Sort results."),
] = None,
limit: LimitOpt = 10,
expand: ExpandOpt = None,
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""List models on the Hub."""
api = get_hf_api(token=token)
sort_key = sort.value if sort else None
results = [
api_object_to_dict(model_info)
for model_info in api.list_models(
filter=filter,
author=author,
search=search,
num_parameters=num_parameters,
sort=sort_key,
limit=limit,
expand=expand, # type: ignore
)
]
out.table(results)
@models_cli.command(
"info",
examples=[
"hf models info meta-llama/Llama-3.2-1B-Instruct",
"hf models info Qwen/Qwen3.5-9B --expand downloads,likes,tags",
],
)
def models_info(
model_id: Annotated[str, typer.Argument(help="The model ID (e.g. `username/repo-name`).")],
revision: RevisionOpt = None,
expand: ExpandOpt = None,
format: FormatWithAutoOpt = OutputFormatWithAuto.auto,
token: TokenOpt = None,
) -> None:
"""Get info about a model on the Hub."""
api = get_hf_api(token=token)
try:
info = api.model_info(repo_id=model_id, revision=revision, expand=expand) # type: ignore
except RepositoryNotFoundError as e:
raise CLIError(f"Model '{model_id}' not found.") from e
except RevisionNotFoundError as e:
raise CLIError(f"Revision '{revision}' not found on '{model_id}'.") from e
out.dict(info)