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| import gradio as gr | |
| import torch | |
| from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, DistilBertForSequenceClassification | |
| modelName = "Pendrokar/TorchMoji" | |
| distil_tokenizer = AutoTokenizer.from_pretrained(modelName) | |
| distil_model = AutoModelForSequenceClassification.from_pretrained(modelName, problem_type="multi_label_classification") | |
| pipeline = pipeline(task="text-classification", model=distil_model, tokenizer=distil_tokenizer) | |
| def predict(deepmoji_analysis): | |
| predictions = pipeline(deepmoji_analysis) | |
| return deepmoji_analysis, {p["label"]: p["score"] for p in predictions} | |
| gradio_app = gr.Interface( | |
| fn=predict, | |
| inputs="text", | |
| outputs="text", | |
| examples=[ | |
| "This GOT show just remember LOTR times!", | |
| "Man, can't believe that my 30 days of training just got a NaN loss", | |
| "I couldn't see 3 Tom Hollands coming...", | |
| "There is nothing better than a soul-warming coffee in the morning", | |
| "I fear the vanishing gradient", "deberta" | |
| ] | |
| ) | |
| if __name__ == "__main__": | |
| gradio_app.launch() |