huggingface_hub 安装部署问题汇总

目录

解决方法，修改Model：

---

pip install huggingface_hub

jsonnano系统 yolo报错：

class Model(nn.Module, PyTorchModelHubMixin, repo_url="https://github.com/ultralytics/ultralytics", pipeline_tag="object-detection", license="agpl-3.0"):

Installing backend dependencies ... errorERROR: Command errored out with exit status 1:command: /usr/bin/python3 /usr/lib/python3/dist-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-3zkfga5a/normal --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- puccinialincwd: NoneComplete output (2 lines):ERROR: Could not find a version that satisfies the requirement puccinialin (from versions: none)ERROR: No matching distribution found for puccinialin----------------------------------------
ERROR: Command errored out with exit status 1: /usr/bin/python3 /usr/lib/python3/dist-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-3zkfga5a/normal --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- puccinialin Check the logs for full command output.

解决方法，修改Model：

class Model(nn.Module):  # 只继承 nn.Module，移除 PyTorchModelHubMixindef __init__(self,model: Union[str, Path] = "yolo11n.pt",task: str = None,verbose: bool = False,) -> None:# 只调用 nn.Module 的 __init__nn.Module.__init__(self)self.callbacks = callbacks.get_default_callbacks()self.predictor = None  # reuse predictorself.model = None  # model objectself.trainer = None  # trainer objectself.ckpt = {}  # if loaded from *.ptself.cfg = None  # if loaded from *.yamlself.ckpt_path = Noneself.overrides = {}  # overrides for trainer objectself.metrics = None  # validation/training metricsself.session = None  # HUB session - 可以保留但不再使用self.task = task  # task typemodel = str(model).strip()# 移除或注释掉 HUB 模型检查部分# if self.is_hub_model(model):#     # Fetch model from HUB#     checks.check_requirements("hub-sdk>=0.0.12")#     session = HUBTrainingSession.create_session(model)#     model = session.model_file#     if session.train_args:  # training sent from HUB#         self.session = session# Check if Triton Server modelif self.is_triton_model(model):self.model_name = self.model = modelself.overrides["task"] = task or "detect"  # set `task=detect` if not explicitly setreturn# Load or create new YOLO modelif Path(model).suffix in {".yaml", ".yml"}:self._new(model, task=task, verbose=verbose)else:self._load(model, task=task)