I have a problem  trained model with tensorflow on transformer pipeline male error
Author: danial1995
Pull request: no

<details><summary>Click to expand!</summary> 
 
 ### 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_</details>

Comments:
You are using a Keras model here, but the `pipeline` can only deal with `TFPreTrainedModel`s (models of the Transformers library).

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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