How pipeline can use a  ner finetuned model from a local directory ?
## ❓ Questions & Help

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Hi, 
I fine tuned XLM-Roberta on my own NER dataset so I got a folder containing pytorch_model.bin and all the other stuff.
But the problem is that I do not figure out how to use this model with the pipeline.
Below is an example of how I used it and the generated error:
Usage:
nlp = pipeline('ner',model= XLMRobertaForTokenClassification.from_pretrained('./1-out/checkpoint-24924/'))
Error:
OSError: Model name './1-out/checkpoint-24924/' was not found in model name list (xlm-roberta-base, ...)

Instead of XLMRobertaForTokenClassification I tried AutoModel and PreTrainedModel but I still get the same error. I also added tokenizer=AutoTokenizer.from_pretrained, etc but with no luck.

Any help is appreciated!
Thank you!
Hi,
Just an update on this issue. I managed to get it work like this:
`model = XLMRobertaForTokenClassification.from_pretrained('./2-out/')`
`tokenizer = XLMRobertaTokenizer.from_pretrained('./2-out/')`
`nlp = pipeline('ner',model= model,tokenizer=tokenizer)`
`nlp('blabla').`

The problem is that the output gives labels for individual tokens and not for complete words. This issue was mentioned also [here](https://github.com/huggingface/transformers/issues/2488).<|||||>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.
