How to load a fine-tuned model and do predictions?
I have fine-tuned a Named entity recognition BERT model using the example here
https://github.com/huggingface/transformers/tree/master/examples/pytorch/token-classification

The command I used is:
 python3 run_ner.py --config_name (The bert model I chose) --tokenizer_name (The bert model I chose) --model_name_or_path (The bert model I chose) --train_file (My train file) --(my validation file)  --text_column_name Words --label_column_name Tags --output_dir output --do_train --do_eval 




I successfully obtained the output, which is  config.json and model.h5

With this, how can I load my model (the model.h5 above) and make a prediction, on an example sentence such as "I visited Github today"?


For the tutorial in the link above, the code has the "do_predict" option, but I do not know how to ask the "run_ner.py" code to load my fine-tuned model, and I want to see the predictions (instead of the code giving me a metrics of accuracy = xx%, precision = xx%.


Thanks.
Hi, please use the [forum](https://discuss.huggingface.co/) to post such general questions, we use issues for bug reports and feature requests. Thank you!<|||||>You can check out [this post](https://discuss.huggingface.co/t/decoding-the-predicted-output-array-in-distilbertbase-uncased-model-for-ner/10673/2?u=nielsr) I wrote on the forum about performing inference with NER models.<|||||>> Hi, please use the [forum](https://discuss.huggingface.co/) to post such general questions, we use issues for bug reports and feature requests. Thank you!

Apologies, I am quite new here. Please close my post if necessary.<|||||>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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.