| from transformers import Pipeline | |
| from transformers.pipelines import PIPELINE_REGISTRY | |
| class Pipeline_One(Pipeline): | |
| def _sanitize_parameters(self, **kwargs): | |
| # Add any additional parameter handling if necessary | |
| return {}, {}, {} | |
| def preprocess(self, text, **kwargs): | |
| return text | |
| def _forward(self, inputs): | |
| model_output = self.model.predict(**inputs, k=1) | |
| return model_output | |
| def postprocess(self, outputs, **kwargs): | |
| return outputs | |
| # Register the pipeline | |
| PIPELINE_REGISTRY.register_pipeline( | |
| "language-detection", | |
| pipeline_class=Pipeline_One, | |
| ) | |