OSError using FlauBERT
Hello everyone,

I'm trying to run Flaubert model on my data using ktrain.


# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...):  flaubert/flaubert_base_cased

Language I am using the model on (English, Chinese ...): French

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

I'm using ktrain to load my model. 
After preprocess my data when i want to get the classifier with function get_classifier() i get this error :

---------------------------------------------------------------------------
```
OSError                                   Traceback (most recent call last)
~\Anaconda3\lib\site-packages\transformers\modeling_tf_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    461                 if resolved_archive_file is None:
--> 462                     raise EnvironmentError
    463             except EnvironmentError:

OSError: 

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
~\Anaconda3\lib\site-packages\ktrain\text\preprocessor.py in _load_pretrained(self, mname, num_labels)
    958             try:
--> 959                 model = self.model_type.from_pretrained(mname, config=self.config)
    960             except:

~\Anaconda3\lib\site-packages\transformers\modeling_tf_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
   1046             if isinstance(config, config_class):
-> 1047                 return model_class.from_pretrained(pretrained_model_name_or_path, *model_args, config=config, **kwargs)
   1048         raise ValueError(

~\Anaconda3\lib\site-packages\transformers\modeling_tf_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    468                 )
--> 469                 raise EnvironmentError(msg)
    470             if resolved_archive_file == archive_file:

OSError: Can't load weights for 'flaubert/flaubert_base_cased'. Make sure that:

- 'flaubert/flaubert_base_cased' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'flaubert/flaubert_base_cased' is the correct path to a directory containing a file named one of tf_model.h5, pytorch_model.bin.



During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
~\Anaconda3\lib\site-packages\ktrain\text\preprocessor.py in _load_pretrained(self, mname, num_labels)
    961                 try:
--> 962                     model = self.model_type.from_pretrained(mname, config=self.config, from_pt=True)
    963                 except:

~\Anaconda3\lib\site-packages\transformers\modeling_tf_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
   1046             if isinstance(config, config_class):
-> 1047                 return model_class.from_pretrained(pretrained_model_name_or_path, *model_args, config=config, **kwargs)
   1048         raise ValueError(

~\Anaconda3\lib\site-packages\transformers\modeling_tf_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    481             # Load from a PyTorch checkpoint
--> 482             return load_pytorch_checkpoint_in_tf2_model(model, resolved_archive_file, allow_missing_keys=True)
    483 

~\Anaconda3\lib\site-packages\transformers\modeling_tf_pytorch_utils.py in load_pytorch_checkpoint_in_tf2_model(tf_model, pytorch_checkpoint_path, tf_inputs, allow_missing_keys)
     92     return load_pytorch_weights_in_tf2_model(
---> 93         tf_model, pt_state_dict, tf_inputs=tf_inputs, allow_missing_keys=allow_missing_keys
     94     )

~\Anaconda3\lib\site-packages\transformers\modeling_tf_pytorch_utils.py in load_pytorch_weights_in_tf2_model(tf_model, pt_state_dict, tf_inputs, allow_missing_keys)
    124     if tf_inputs is not None:
--> 125         tf_model(tf_inputs, training=False)  # Make sure model is built
    126 

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py in __call__(self, inputs, *args, **kwargs)
    821               self._compute_dtype):
--> 822             outputs = self.call(cast_inputs, *args, **kwargs)
    823           self._handle_activity_regularization(inputs, outputs)

~\Anaconda3\lib\site-packages\transformers\modeling_tf_xlm.py in call(self, inputs, attention_mask, langs, token_type_ids, position_ids, lengths, cache, head_mask, inputs_embeds, output_attentions, output_hidden_states, labels, training)
    803             output_hidden_states=output_hidden_states,
--> 804             training=training,
    805         )

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py in __call__(self, inputs, *args, **kwargs)
    821               self._compute_dtype):
--> 822             outputs = self.call(cast_inputs, *args, **kwargs)
    823           self._handle_activity_regularization(inputs, outputs)

~\Anaconda3\lib\site-packages\transformers\modeling_tf_flaubert.py in call(self, inputs, attention_mask, langs, token_type_ids, position_ids, lengths, cache, head_mask, inputs_embeds, training, output_attentions, output_hidden_states)
    259             if not self.pre_norm:
--> 260                 attn_outputs = self.attentions[i]([tensor, attn_mask, None, cache, head_mask[i]], training=training)
    261                 attn = attn_outputs[0]

~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py in __call__(self, inputs, *args, **kwargs)
    821               self._compute_dtype):
--> 822             outputs = self.call(cast_inputs, *args, **kwargs)
    823           self._handle_activity_regularization(inputs, outputs)

~\Anaconda3\lib\site-packages\transformers\modeling_tf_xlm.py in call(self, inputs, training)
    140         """
--> 141         input, mask, kv, cache, head_mask, output_attentions = inputs
    142         # Input is (bs, qlen, dim)

ValueError: not enough values to unpack (expected 6, got 5)

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-38-dc13d8280fd1> in <module>
----> 1 model = t.get_classifier()

~\Anaconda3\lib\site-packages\ktrain\text\preprocessor.py in get_classifier(self, fpath, multilabel, metrics)
    997         num_labels = len(self.get_classes())
    998         mname = fpath if fpath is not None else self.model_name
--> 999         model = self._load_pretrained(mname, num_labels)
   1000         if multilabel:
   1001             loss_fn =  keras.losses.BinaryCrossentropy(from_logits=True)

~\Anaconda3\lib\site-packages\ktrain\text\preprocessor.py in _load_pretrained(self, mname, num_labels)
    962                     model = self.model_type.from_pretrained(mname, config=self.config, from_pt=True)
    963                 except:
--> 964                     raise ValueError('could not load pretrained model %s using both from_pt=False and from_pt=True' % (mname))
    965         else:
    966             model = self.model_type.from_pretrained(mname, num_labels=num_labels)

ValueError: could not load pretrained model flaubert/flaubert_base_cased using both from_pt=False and from_pt=True
```

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.0.2
- Platform: windows 10
- Python version: 3.8
- PyTorch version (No GPU): 1.0.0
- Tensorflow version (No GPU): 2.1.0
- Using GPU in script?: No
- Using distributed or parallel set-up in script?:

Thank you a lot for your help
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
