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| import streamlit as st | |
| from transformers import AutoProcessor, SeamlessM4TModel | |
| st.title("Ed's not working Hot Dog? Or Not!!!!!?") | |
| processor = AutoProcessor.from_pretrained("facebook/hf-seamless-m4t-large") | |
| model = SeamlessM4TModel.from_pretrained("facebook/hf-seamless-m4t-large") | |
| if "texttotranslate" not in st.session_state: | |
| st.session_state.texttotranslate = "" | |
| def submit(): | |
| st.write('method') | |
| st.session_state.texttotranslate = st.session_state.widget | |
| text_inputs = processor(text = st.session_state.texttotranslate, src_lang="eng", return_tensors="pt") | |
| output_tokens = model.generate(**text_inputs, tgt_lang="fra", generate_speech=False) | |
| translated_text_from_text = processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True) | |
| st.write(translated_text_from_text) | |
| st.text_input('hello', value="fat cats", key="widget", on_change=submit) | |
| #text_inputs = processor(text = title, src_lang="eng", return_tensors="pt") | |
| # from text | |
| #output_tokens = model.generate(**text_inputs, tgt_lang="fra", generate_speech=False) | |
| #translated_text_from_text = processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True) | |
| #st.write(translated_text_from_text) | |
| st.write("fool me") | |