import gradio as gr from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification import time model_name = "ethanrom/a2" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForSequenceClassification.from_pretrained(model_name) pretrained_model_name = "roberta-large-mnli" pretrained_tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name) pretrained_model = pipeline("zero-shot-classification", model=pretrained_model_name, tokenizer=pretrained_tokenizer) candidate_labels = ["negative", "positive", "no impact", "mixed"] def predict_sentiment(text_input, model_selection): if model_selection == "Fine-tuned": inputs = tokenizer.encode_plus(text_input, return_tensors='pt') start_time = time.time() outputs = model(**inputs) end_time = time.time() logits = outputs.logits.detach().cpu().numpy()[0] predicted_class = int(logits.argmax()) inference_time = end_time - start_time model_size = model.num_parameters() return candidate_labels[predicted_class], inference_time, model_size else: start_time = time.time() result = pretrained_model(text_input, candidate_labels) end_time = time.time() predicted_class = result["labels"][0] inference_time = end_time - start_time model_size = pretrained_model.model.num_parameters() return predicted_class, inference_time, model_size inputs = [ gr.inputs.Textbox("Enter text"), gr.inputs.Dropdown(["Pretrained", "Fine-tuned"], label="Select model"), ] outputs = [ gr.outputs.Textbox(label="Predicted Sentiment"), gr.outputs.Textbox(label="Inference Time (s)"), gr.outputs.Textbox(label="Model Size (params)"), ] gr.Interface(fn=predict_sentiment, inputs=inputs, outputs=outputs, title="Sentiment Analysis", description="roberta-large-mnli fine tuned with poem_sentiment dataset for sentiment analysis", examples=[ ["max laid his hand upon the old man's arm", "Pretrained"], ["the red sword sealed their vows!", "Fine-tuned"], ["and that is why, the lonesome day,", "Pretrained"], ["it flows so long as falls the rain", "Fine-tuned"], ["thy hands all cunning arts that women prize", "Pretrained"], ["on us lift up the light", "Fine-tuned"], ],).launch();