Config File
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## Details
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Hi everybody, is there a way to automatically obtain the configuration file for pre-trained TensorFlow T5 network? Specifically the config.json file which I want to use to convert a tf model into pytorch using the script provided by HuggingFace.
Just to be more clear, I want something like that: https://s3.amazonaws.com/models.huggingface.co/bert/t5-small-config.json, with the specifications for my model.

Thanks in advance :)


You get the default config file as written on AWS with 
```python 
config = T5Config.from_pretrained("t5-small")
```

If you want to change anything on the config after you can update it with a dict of your specifications:
```python 
config.update(your_dict)
```<|||||>Hello @patrickvonplaten !
I have tried to update the config file using new dict 
```
new_dict={  "d_ff": 2048,
        "d_kv": 64,
        "d_model": 512,
        "dropout_rate": 0.1,
        "eos_token_id": 1,
        "feed_forward_proj": "relu",
        "initializer_factor": 1.0,
        "is_encoder_decoder": True,
        "layer_norm_epsilon": 1e-06,
        "model_type": "t5",
        "num_decoder_layers": 6,
        "num_heads": 8,
        "num_layers": 6,
        "pad_token_id": 0,
        "relative_attention_num_buckets": 32,
        "transformers_version": "4.5.1",
        "use_cache": False,
        "vocab_size": 32128,
        "num_input_sent": 4,   # TODO: ADDED
        "max_source_len ": 25, # TODO: ADDED
        "max_target_len": 25,  # TODO: ADDED
        
     }
```
print(onfig.d_ff)  gives 2048

but:  
print(max_source_len) gives me an error  "AttributeError: 'T5Config' object has no attribute 'max_source_len'"

how to use the new added configurations after they are added?<|||||>Hey @Arij-Aladel, 

What would be the purpose of adding parameters to the config, such as `max_target_len` that are not used in the corresponding model `T5Model`?<|||||>@patrickvonplaten  I am trying to build my model depending on t5 hugging face API and I need to build my own config. Whatever the purpose is , the question still what is th benefit of updating the parameters if I can not reuse them?<|||||>Ok thanks I have solved it it was my bad, so sorry! every thing works well