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Llama-4-Scout-17B-16E-Instruct

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NameError Traceback (most recent call last)
Cell In[6], line 5
2 from transformers import AutoProcessor, AutoModelForImageTextToText
4 processor = AutoProcessor.from_pretrained("meta-llama/Llama-4-Scout-17B-16E-Instruct")
----> 5 model = AutoModelForImageTextToText.from_pretrained("meta-llama/Llama-4-Scout-17B-16E-Instruct")

File /usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py:571, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
569 if model_class.config_class == config.sub_configs.get("text_config", None):
570 config = config.get_text_config()
--> 571 return model_class.from_pretrained(
572 pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
573 )
574 raise ValueError(
575 f"Unrecognized configuration class {config.class} for this kind of AutoModel: {cls.name}.\n"
576 f"Model type should be one of {', '.join(c.name for c in cls._model_mapping.keys())}."
577 )

File /usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:279, in restore_default_torch_dtype.._wrapper(*args, **kwargs)
277 old_dtype = torch.get_default_dtype()
278 try:
--> 279 return func(*args, **kwargs)
280 finally:
281 torch.set_default_dtype(old_dtype)

File /usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:4333, in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)
4330 config.name_or_path = pretrained_model_name_or_path
4332 # Instantiate model.
-> 4333 model_init_context = cls.get_init_context(is_quantized, _is_ds_init_called)
4335 config = copy.deepcopy(config) # We do not want to modify the config inplace in from_pretrained.
4336 if not getattr(config, "_attn_implementation_autoset", False):

File /usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:3736, in PreTrainedModel.get_init_context(cls, is_quantized, _is_ds_init_called)
3734 init_contexts.append(set_quantized_state())
3735 else:
-> 3736 init_contexts = [no_init_weights(), init_empty_weights()]
3738 return init_contexts

NameError: name 'init_empty_weights' is not defined