| import gradio as gr | |
| from transformers import pipeline | |
| def process_swedish_text(text): | |
| # Models from https://huggingface.co/models | |
| # https://huggingface.co/KBLab/bert-base-swedish-cased-ner | |
| ml_model = 'KBLab/bert-base-swedish-cased-ner' | |
| ner_pipeline = pipeline(model=ml_model, task='ner') | |
| # Run NER | |
| pipeline_results = ner_pipeline(text) | |
| print('NER results:', pipeline_results) | |
| # Return values | |
| return pipeline_results | |
| gradio_interface = gr.Interface(fn=process_swedish_text, inputs="text", outputs="json") | |
| gradio_interface.launch() | |