Hi,
Thank you for your reply. I tried this approach and got this error:



OSError: Error no file named [‘pytorch_model.bin’, ‘tf_model.h5’, ‘model.ckpt.index’, ‘flax_model.msgpack’] found in directory hub_models/ena_all_9010/anatomy/4e-05-90 or from_tf and from_flax set to False.



I was thinking of a way to convert the checkpoints of tensorflow fine-tuned model to pytorch as I did with the checkpoints for pretrained Bert models. Here are the files of one Bert fine-tuned model:

checkpoint
config.json
eval
eval_results.txt
eval.tf_record
graph.pbtxt
label2id.pkl
label_test.txt
model.ckpt-3000.data-00000-of-00001
model.ckpt-3000.index
model.ckpt-3000.meta
model.ckpt-4000.data-00000-of-00001
model.ckpt-4000.index
model.ckpt-4000.meta
model.ckpt-5000.data-00000-of-00001
model.ckpt-5000.index
model.ckpt-5000.meta
model.ckpt-6000.data-00000-of-00001
model.ckpt-6000.index
model.ckpt-6000.meta
model.ckpt-6316.data-00000-of-00001
model.ckpt-6316.index
model.ckpt-6316.meta
NER_result_conll.txt
predict.tf_record
token_test.txt
train.tf_record

I tried to convert the checkpoints using convert_bert_original_tf_checkpoint_to_pytorch.py but I got the following error:

raise ModuleAttributeError("’{}’ object has no attribute ‘{}’".format(
torch.nn.modules.module.ModuleAttributeError: ‘BertForPreTraining’ object has no attribute ‘bias’

I tried to fix it by replacing line 33 with  model = BertForTokenClassification(config), then I got the following error:

transformers/src/transformers/models/bert/modeling_bert.py", line 156, in load_tf_weights_in_bert
if pointer.shape != array.shape:
AttributeError: ‘NoneType’ object has no attribute ‘shape’

investigating this issue more showed that pointer.shape != array.shape. Infact pointer = None for the following layers:
[‘bert’, ‘pooler’, ‘dense’, ‘bias’] , where array.shape = (768,)
[‘bert’, ‘pooler’, ‘dense’, ‘kernel’], where array.shape = (768, 768)
[‘output_bias’], where array.shape = (7,)
[‘output_weights’], where array.shape = (7, 768)
I’d appreciate if someone can help me in figuring out how to fix the pointer for those layers.
Thanks