import streamlit as st from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline from diffusers import StableDiffusionPipeline import torch st.set_page_config( page_title="Tamil Creative Studio", page_icon="🇮🇳", layout="centered", ) def load_css(): st.markdown( """""", unsafe_allow_html=True, ) @st.cache_resource(show_spinner=False) def load_all_models(): model_id = "ai4bharat/indictrans2-indic-en-dist-200M" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForSeq2SeqLM.from_pretrained(model_id) text_gen = pipeline("text-generation", model="gpt2", device=-1) img_pipe = StableDiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-2-base", torch_dtype=torch.float32, safety_checker=None ).to("cpu") return tokenizer, model, text_gen, img_pipe def translate_tamil(text, tokenizer, model): inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=128) outs = model.generate(**inputs, max_length=150, num_beams=5, early_stopping=True) return tokenizer.decode(outs[0], skip_special_tokens=True) def main(): load_css() st.markdown( '
Translate Tamil text and generate creative content