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Update acestep/gradio_ui/interfaces/generation.py
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Update acestep/llm_inference.py
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Update acestep/gradio_ui/events/results_handlers.py
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Update acestep/gradio_ui/__init__.py
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Create acestep/gradio_ui/resume_wiring.py
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Update acestep/inference.py
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Update acestep/resume_utils.py
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Update acestep/gradio_ui/resume_wiring.py
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Create acestep/gradio_ui/resume_wiring.py
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Update acestep/gradio_ui/__init__.py
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Create acestep/resume_utils.py
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Update acestep/llm_inference.py
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Update acestep/inference.py
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Update acestep/inference.py
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Update acestep/llm_inference.py
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Update acestep/llm_inference.py
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Update acestep/gradio_ui/events/results_handlers.py
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Update acestep/gradio_ui/events/generation_handlers.py
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Update acestep/gradio_ui/events/results_handlers.py
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Update acestep/gradio_ui/events/results_handlers.py
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Update acestep/inference.py
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Update acestep/handler.py
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Update acestep/handler.py
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Update acestep/gradio_ui/events/generation_handlers.py
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Update acestep/inference.py
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fix: download unified repo for shared components when using independent model repos
XL models are in separate repos without VAE/text encoder. Ensure the unified repo (ACE-Step/Ace-Step1.5) is downloaded first to provide shared components (vae, Qwen3-Embedding-0.6B, silence_latent).7403460 -
feat: add XL (4B DiT) turbo as default model + acemusic banner
- Default model 1: acestep-v15-xl-turbo (was acestep-v15-turbo) - Default model 2: acestep-v15-turbo (was acestep-v15-turbo-shift3) - Add XL model entries to MODEL_REPO_MAPPING for auto-download - Enhanced acemusic.ai banner with gradient background - Update README frontmatter with XL model9d632db
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fix: lower ZeroGPU duration to 120s for free-tier users
All @spaces.GPU(duration=...) decorators exceeded the free-tier ZeroGPU maximum, causing instant rejection before generation starts. Lowered all durations from 180-300s to 120s to fix the error: 'The requested GPU duration (300s) is larger than the maximum allowed' Fixes: community reported issue on HuggingFace Spaced32ba2d
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fix: move @spaces.GPU decorators to local wrappers to fix ZeroGPU pickling error
On ZeroGPU, Gradio serializes (pickles) event handler functions to send them to GPU worker processes. When fn= was a lambda capturing dit_handler, Python tried to pickle the entire handler including AceStepDiTModel which contains unpicklable local objects in __init__, causing: 'Can't pickle local object AceStepDiTModel.__init__' Fix: Remove @_get_spaces_gpu_decorator from module-level functions and instead apply it to local wrapper functions defined inside setup_event_handlers(), passed directly as fn= (same pattern as the working generation_wrapper). Affected handlers: - process_source_audio (Analyze button) - handle_create_sample (Create Sample button) - handle_format_sample (Format button) - calculate_score_handler_with_selection (Score buttons) - generate_lrc_handler (LRC buttons)6813c41
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fix is_flash_attention_available
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switch to zero gpu
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resolve intermittent CUDA assertion error in concurrent serving scenarios
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fix max audio code id
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reverse fix
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fix max audio code id
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update tech report link
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add acemusic link
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fix cfg kv block allocate
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enforce upload audio duration limits
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fix duration
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set default_concurrency_limit & set bs=2 no interactive
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bigger sample btn
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load audio fallback
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fix torchcodec ffmpeg
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fix CUDA Graph mismatch in nanovllm
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fix cover load src audio using ffmpeg
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hide files list
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support shift3 download
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update project page url
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