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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") | |