Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import urllib.parse | |
| # Set Streamlit page configuration | |
| st.set_page_config( | |
| page_title="Text-to-Music Generator π΅", | |
| page_icon="π΅", | |
| layout="wide", | |
| initial_sidebar_state="expanded", | |
| ) | |
| # Add custom CSS for styling | |
| st.markdown(""" | |
| <style> | |
| body { | |
| background-color: #eaf6fb; | |
| color: #003366; | |
| font-family: 'Arial', sans-serif; | |
| } | |
| .stButton>button { | |
| background-color: #4dabf5; | |
| color: white; | |
| font-weight: bold; | |
| border-radius: 12px; | |
| padding: 10px 20px; | |
| } | |
| .stButton>button:hover { | |
| background-color: #007bb5; | |
| } | |
| .stTextArea textarea { | |
| border: 2px solid #4dabf5; | |
| border-radius: 8px; | |
| } | |
| iframe { | |
| border: 2px solid #4dabf5; | |
| border-radius: 8px; | |
| } | |
| .title { | |
| text-align: center; | |
| font-size: 36px; | |
| font-weight: bold; | |
| color: #003366; | |
| } | |
| .description { | |
| text-align: center; | |
| font-size: 18px; | |
| color: #005792; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # Initialize the Hugging Face model and tokenizer | |
| def load_model(): | |
| tokenizer = AutoTokenizer.from_pretrained('sander-wood/text-to-music') | |
| model = AutoModelForSeq2SeqLM.from_pretrained('sander-wood/text-to-music') | |
| return tokenizer, model | |
| # Load model and tokenizer | |
| tokenizer, model = load_model() | |
| # Streamlit App UI | |
| st.markdown("<div class='title'>π΅ Text-to-Music Generator π΅</div>", unsafe_allow_html=True) | |
| st.markdown(""" | |
| <div class='description'> | |
| Enter a textual description, and the model will generate music in ABC notation. | |
| You can use tools like [abc2midi](http://abc.sourceforge.net/abcMIDI/) to convert the notation into a playable file. | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Input Fields | |
| with st.container(): | |
| text_input = st.text_area( | |
| "Enter a description for the music:", | |
| placeholder="e.g., This is a traditional Irish dance music.", | |
| ) | |
| max_length = st.slider( | |
| "Maximum Length of Generated Music:", min_value=128, max_value=2048, value=1024, step=128 | |
| ) | |
| top_p = st.slider( | |
| "Top-p (Nucleus Sampling):", min_value=0.1, max_value=1.0, value=0.9, step=0.05 | |
| ) | |
| temperature = st.slider( | |
| "Temperature (Sampling Diversity):", min_value=0.1, max_value=2.0, value=1.0, step=0.1 | |
| ) | |
| # Generate Music Button | |
| if st.button("Generate Music πΆ"): | |
| if not text_input.strip(): | |
| st.error("Please enter a valid description!") | |
| else: | |
| st.info("Generating music... This might take a few seconds.") | |
| try: | |
| # Tokenize input | |
| input_ids = tokenizer(text_input, return_tensors='pt', truncation=True, max_length=max_length)['input_ids'] | |
| # Generate music using efficient beam search sampling | |
| generated_ids = model.generate( | |
| input_ids, | |
| max_length=max_length, | |
| do_sample=True, | |
| top_p=top_p, | |
| temperature=temperature, | |
| eos_token_id=tokenizer.eos_token_id, | |
| ) | |
| # Decode generated music | |
| tune = tokenizer.decode(generated_ids[0], skip_special_tokens=True) | |
| tune = "X:1\n" + tune | |
| st.success("Music generated successfully!") | |
| # Display raw generated music in the app | |
| st.text_area("Generated Music (ABC Notation):", value=tune, height=300) | |
| # Encode tune for URL and embed ABCJS Editor | |
| encoded_tune = urllib.parse.quote(tune) | |
| editor_url = f"https://www.abcjs.net/abcjs-editor?abc={encoded_tune}" | |
| st.markdown(f""" | |
| ### ABCJS Editor Preview | |
| You can edit or play the music below: | |
| <iframe src="{editor_url}" width="100%" height="500" style="border:none;"></iframe> | |
| """, unsafe_allow_html=True) | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |