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src/streamlit_app.py
Browse files- src/streamlit_app.py +25 -39
src/streamlit_app.py
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import altair as alt
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import numpy as np
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import pandas as pd
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import streamlit as st
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"rand": np.random.randn(num_points),
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})
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st.altair_chart(alt.Chart(df, height=700, width=700)
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.mark_point(filled=True)
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.encode(
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x=alt.X("x", axis=None),
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y=alt.Y("y", axis=None),
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color=alt.Color("idx", legend=None, scale=alt.Scale()),
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size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
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))
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import streamlit as st
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from huggingface_hub import hf_hub_download
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import torch
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# Télécharger le modèle
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model_path = hf_hub_download(
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repo_id="tencent/SongGeneration",
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filename="ckpt/songgeneration_base_zh/model.pt"
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)
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# Charger le modèle
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model = torch.load(model_path)
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model.eval()
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# Interface Streamlit
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st.title("🎵 Générateur de Chansons")
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description = st.text_area("Décrivez l'ambiance de la chanson")
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if st.button("Générer la chanson"):
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if description:
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# Génération de la chanson (à adapter selon le modèle)
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chanson = model.generate(description)
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st.audio(chanson)
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else:
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st.warning("Veuillez fournir une description.")
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