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| 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(); |