I have a problem trained model with tensorflow on transformer pipeline male error

[danial1995]

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### Issue Type Bug ### Have you reproduced the bug with TF nightly? Yes ### Source source ### Tensorflow Version 2.8 ### Custom Code Yes ### OS Platform and Distribution _No response_ ### Mobile device _No response_ ### Python version _No response_ ### Bazel version _No response_ ### GCC/Compiler version _No response_ ### CUDA/cuDNN version _No response_ ### GPU model and memory _No response_ ### Current Behaviour? i’m using this github text summarization and I have a problem. I have been struggling for two week and I could not figure that out. im using a notebook from this github repository: https://github.com/flogothetis/Abstractive-Summarization-T5-Keras notebook link: https://github.com/flogothetis/Abstractive-Summarization-T5-Keras/blob/main/AbstractiveSummarizationT5.ipynb after train model i wanna use huggingface transformer pipe line to generate summerization **from transformers import pipeline summarizer = pipeline(“summarization”, model=model, tokenizer=“t5-small”, framework=“tf”) summarizer(“some text”)** but it pop out an error: **AttributeError: ‘Functional’ object has no attribute 'config’** Anyone has any idea how can i solve it? full error: AttributeError Traceback (most recent call last) /tmp/ipykernel_20/1872405895.py in ----> 1 summarizer = pipeline(“summarization”, model=model, tokenizer=“t5-small”, framework=“tf”) 2 3 summarizer(“The US has passed the peak on new coronavirus cases, President Donald Trump said and predicted that some states would reopen”) /opt/conda/lib/python3.7/site-packages/transformers/pipelines/init.py in pipeline(task, model, config, tokenizer, framework, revision, use_fast, use_auth_token, model_kwargs, **kwargs) 432 break 433 → 434 return task_class(model=model, tokenizer=tokenizer, modelcard=modelcard, framework=framework, task=task, **kwargs) /opt/conda/lib/python3.7/site-packages/transformers/pipelines/text2text_generation.py in init(self, *args, **kwargs) 37 38 def init(self, *args, **kwargs): —> 39 super().init(*args, **kwargs) 40 41 self.check_model_type( /opt/conda/lib/python3.7/site-packages/transformers/pipelines/base.py in init(self, model, tokenizer, modelcard, framework, task, args_parser, device, binary_output) 548 549 # Update config with task specific parameters → 550 task_specific_params = self.model.config.task_specific_params 551 if task_specific_params is not None and task in task_specific_params: 552 self.model.config.update(task_specific_params.get(task)) AttributeError: ‘Functional’ object has no attribute 'config’ ``` ### Standalone code to reproduce the issue ```shell summarizer = pipeline(“summarization”, model=model, tokenizer=“t5-small”, framework=“tf”) summarizer(“some text”) but it pop out an error: AttributeError: ‘Functional’ object has no attribute 'config’ ``` ### Relevant log output _No response_

[sgugger]

You are using a Keras model here, but the pipeline can only deal with TFPreTrainedModels (models of the Transformers library).

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