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57eb232 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch
MODEL_PATH = "."
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_PATH)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
def resumebot(question):
prompt = f"Answer this resume question: {question}"
inputs = tokenizer(
prompt,
return_tensors="pt",
truncation=True,
max_length=256
).to(device)
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=100,
num_beams=4,
early_stopping=True
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
demo = gr.Interface(
fn=resumebot,
inputs=gr.Textbox(
lines=2,
placeholder="Ask something about Vaishnavi's resume..."
),
outputs=gr.Textbox(label="ResumeBot Answer"),
title="Vaishnavi ResumeBot",
description="Ask questions about education, skills, projects and experience."
)
if __name__ == "__main__":
demo.launch()
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