Load weights from MiniMaxAI/MiniMax-Music3

README.md

@@ -4,9 +4,9 @@ emoji: 🎵
 colorFrom: pink
 colorTo: purple
 sdk: gradio
-sdk_version: "6.16.0"
+sdk_version: 6.24.0
 app_file: app.py
-pinned: false
+pinned: true
 suggested_hardware: zero-a10g
 ---
 
@@ -17,8 +17,8 @@ The input surface is a single Suno-inspired custom `gr.HTML` composer (Simple
 chips, structured-caption fields per the official prompting guide) that drives Gradio events via
 `trigger()`/`props.value`; styling uses only theme CSS vars so it follows the Citrus theme natively.
 
-- Weights: `diffusers-internal-dev/MiniMax-Music3-Diffusers` (private)
+- Weights: `MiniMaxAI/MiniMax-Music3`
 - AoTI kernels: `diffusers-internal-dev/MiniMax-Music3-aoti` (compiled on RTX Pro 6000, matching ZeroGPU hardware)
 - Generation streams chunk by chunk with a configurable playback headroom. The 8B language-model stage runs eager
   on ZeroGPU (its JIT StaticCache ladder needs a persistent process); AoTI-exporting the LM decode step per cache
-  bucket is the follow-up that brings the extra ~1.9x.
+  bucket is the follow-up that brings the extra ~1.9x.

app.py

@@ -14,7 +14,7 @@ from huggingface_hub import snapshot_download
 from diffusers import ModularPipeline
 from diffusers.models.modeling_outputs import Transformer2DModelOutput
 
-PIPE = ModularPipeline.from_pretrained("diffusers-internal-dev/MiniMax-Music3-Diffusers")
+PIPE = ModularPipeline.from_pretrained("MiniMaxAI/MiniMax-Music3")
 PIPE.load_components(dtype=torch.bfloat16)
 PIPE.to("cuda")
 
@@ -1550,16 +1550,31 @@ CSS = """
 #col-container { max-width: 1300px; margin: 0 auto; }
 .dark .gradio-container { color: var(--body-text-color); }
 .html-container{padding: 0}
+.mm3-logo { display: block; margin: 8px auto 0; width: 500px; max-width: 100%; }
+.mm3-logo-dark { display: none; }
+.dark .mm3-logo-light { display: none; }
+.dark .mm3-logo-dark { display: block; }
 """
 
+import base64
+
+_LOGO_LIGHT_B64 = base64.b64encode(open("logo_light.png", "rb").read()).decode()
+_LOGO_DARK_B64 = base64.b64encode(open("logo_dark.png", "rb").read()).decode()
+
 with gr.Blocks(theme=gr.themes.Citrus(), css=CSS) as demo:
     with gr.Column(elem_id="col-container"):
+        gr.HTML(
+            '<img src="data:image/png;base64,' + _LOGO_LIGHT_B64 + '" class="mm3-logo mm3-logo-light" alt="MiniMax Music 3">'
+            '<img src="data:image/png;base64,' + _LOGO_DARK_B64 + '" class="mm3-logo mm3-logo-dark" alt="MiniMax Music 3">',
+            container=False,
+            padding=False,
+        )
         gr.Markdown(
-            "# MiniMax Music 3\n"
-            "MiniMax Music 3.0 is a music generation model designed to support the creation of full-length songs. "
-            "[[model]](https://huggingface.co/MiniMaxAI/MiniMax-Music3) "
-            "[[project]](https://minimax-ai.github.io/music3-demo/) "
-            "[[use locally with diffusers]](https://github.com/huggingface/diffusers/blob/82319140e0456fd58beff0a251c38825bfc310de/docs/source/en/api/pipelines/minimax_music3.md)"
+            "MiniMax Music 3 is a music generation model designed to support the creation of full-length songs "
+            "[[prompting guide and skill]](https://huggingface.co/spaces/multimodalart/minimax-music3-prompting-guide) | "
+            "[[model]](https://huggingface.co/MiniMaxAI/MiniMax-Music3) | "
+            "[[project]](https://minimax-ai.github.io/music3-demo/) | "
+            "[[run locally with diffusers]](https://github.com/huggingface/diffusers/blob/82319140e0456fd58beff0a251c38825bfc310de/docs/source/en/api/pipelines/minimax_music3.md)"
         )
         with gr.Row():
             with gr.Column():