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Runtime error
| from clip.clip import tokenize as _tokenize, load as _load, available_models as _available_models | |
| import re | |
| import string | |
| dependencies = ["torch", "torchvision", "ftfy", "regex", "tqdm"] | |
| # For compatibility (cannot include special characters in function name) | |
| model_functions = { model: re.sub(f'[{string.punctuation}]', '_', model) for model in _available_models()} | |
| def _create_hub_entrypoint(model): | |
| def entrypoint(**kwargs): | |
| return _load(model, **kwargs) | |
| entrypoint.__doc__ = f"""Loads the {model} CLIP model | |
| Parameters | |
| ---------- | |
| device : Union[str, torch.device] | |
| The device to put the loaded model | |
| jit : bool | |
| Whether to load the optimized JIT model or more hackable non-JIT model (default). | |
| download_root: str | |
| path to download the model files; by default, it uses "~/.cache/clip" | |
| Returns | |
| ------- | |
| model : torch.nn.Module | |
| The {model} CLIP model | |
| preprocess : Callable[[PIL.Image], torch.Tensor] | |
| A torchvision transform that converts a PIL image into a tensor that the returned model can take as its input | |
| """ | |
| return entrypoint | |
| def tokenize(): | |
| return _tokenize | |
| _entrypoints = {model_functions[model]: _create_hub_entrypoint(model) for model in _available_models()} | |
| globals().update(_entrypoints) |