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| import gradio as gr | |
| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| from textwrap import fill | |
| # Load fine-tuned model and tokenizer | |
| last_checkpoint = "Jyotiyadav/model2.0" | |
| finetuned_model = T5ForConditionalGeneration.from_pretrained(last_checkpoint) | |
| tokenizer = T5Tokenizer.from_pretrained(last_checkpoint) | |
| # Define inference function | |
| def answer_question(question): | |
| # Format input | |
| inputs = ["Please answer this question: " + question] | |
| inputs = tokenizer(inputs, return_tensors="pt") | |
| # Generate answer | |
| outputs = finetuned_model.generate(**inputs) | |
| answer = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| # Wrap answer for better display | |
| return fill(answer, width=80) | |
| # Create Gradio interface | |
| iface = gr.Interface( | |
| fn=answer_question, | |
| inputs="text", | |
| outputs="text", | |
| title="LLM Flan-T5 - Store Sales Prediction(Time Series Forecasting)", | |
| description="We have utilised FLANT-5 Model for Time Series Forecasting", | |
| examples=[ | |
| ["For store number 1 in the city of Quito, with products from various categories such as AUTOMOTIVE, during a 0 on 2017-8-16, with no, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"], | |
| ["For store number 1 in the city of Quito, with products from various categories such as BABY CARE, during a 0 on 2017-8-16, with no, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"], | |
| ["For store number 1 in the city of Quito, with products from various categories such as BEAUTY, during a 0 on 2017-8-16, with promotions, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"], | |
| ["For store number 1 in the city of Quito, with products from various categories such as HOME CARE, during a 0 on 2017-8-16, with promotions, cluster 13, and WTI crude oil price at $46.8, what were the total sales on that day?"] | |
| ] | |
| ) | |
| # Launch Gradio interface | |
| iface.launch() | |