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Yes—you can generate a complete AI song with lead vocals and accompaniment in WanGP by feeding YuE2-3B a style prompt and sectioned lyrics. The documented starting point is a BF16-capable NVIDIA GPU with 24GB of VRAM. In WanGP, you install the application, open its audio workspace, select YuE2, let the required checkpoints download, then generate with a planning mode that controls whether YuE2 creates an editable melody-and-chord score.
For the most controllable first attempt, use cot="full", write concise lyrics with tags such as [Verse] and [Chorus], and save the complete artifact directory rather than only the playable file. That directory preserves the score, plan, tokens, latents, settings and model identities needed to reproduce or revise a result.
What is YuE2-3B, and what does WanGP add?
YuE2-3B is an open music-generation model that turns lyrics and a style description into a song containing vocals and accompaniment. Its workflow can first create a symbolic composition plan for melody and chords, then synthesize audio from that plan. The score is an important control surface: you can inspect or edit the musical plan and render a new recording.
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The result is not a text-to-music preview that stops at a loop. With an appropriate lyric structure and a coherent style prompt, the workflow is intended to produce a full arrangement with sung sections, instrumental backing and a saved composition plan. Output length and completeness still depend on the model’s token limits and the generation settings, so inspect the saved metadata instead of judging only by whether an audio player opens.
What GPU and software do I need for YuE2-3B in WanGP?
YuE2’s upstream generation guide identifies Linux, Python 3.12 and a BF16-capable NVIDIA GPU with 24GB of VRAM as the supported starting point. That is a documented baseline, not a guarantee that every WanGP optimization consumes exactly that amount of memory. WanGP’s quantization choices, attention kernels and GPU-specific runtime guidance can change practical requirements.
| Component | What the documentation establishes | Practical implication |
|---|---|---|
| GPU | BF16-capable NVIDIA graphics card; YuE2’s current supported baseline is 24GB VRAM. | Check your card’s BF16 capability and available memory before downloading checkpoints. A lower-memory configuration may require a WanGP optimization, but it is outside the stated upstream baseline. |
| Operating system and Python | The upstream guide describes Linux with Python 3.12. | WanGP also publishes installation paths for Windows, Linux and macOS. Use the current WanGP instructions for the Python, PyTorch, CUDA, Triton and attention-kernel combination that matches your GPU generation. |
| Internet access | WanGP downloads model checkpoints and optional assets when a selected workflow needs them. | Plan for internet access on first launch or first use of YuE2. A disconnected machine must already have every required file in the expected layout. |
| Disk space | The workflow can retain checkpoints plus audio, scores, plans, tokens and latents. | An NVMe SSD is a sensible performance and capacity choice, but no separate capacity figure is established in the documentation. Keep room for multiple artifact directories if you compare prompts or renders. |
| Listening setup | Headphones are optional for evaluation. | Use headphones or monitors that reveal vocal timing, clipping and masking when you compare versions; they are not a generation prerequisite. |
If you are on Windows or macOS, the existence of a WanGP installer or launcher does not by itself change YuE2’s upstream GPU assumptions. Treat the launcher as an installation route, then follow the GPU-generation notes shown for your selected runtime. If setup reports a missing kernel, incompatible CUDA build or insufficient memory, use those GPU-specific instructions rather than mixing packages from an unrelated installation.
How do I install YuE2 in WanGP?
Use the current WanGP installation guide for your operating system. The labels can change between releases, but the workflow is consistent: install WanGP, open its audio area, select YuE2, and let the application obtain the files required by that model.
- Install WanGP. Choose the official script for Windows, Linux or macOS, or use a documented Pinokio or Windows desktop launcher. Keep the installation in a location with enough free disk space for checkpoints and generated artifacts.
- Start the application. On the first launch, allow the runtime to complete its environment setup. If the installer asks for a GPU-specific PyTorch, CUDA, Triton or attention-kernel option, choose the combination recommended for your installed NVIDIA generation.
- Open the audio workspace. WanGP lists YuE2 among its audio models. Select YuE2 rather than a video or image workflow.
- Download the required files. Approve the checkpoint and optional-asset downloads triggered by the workflow. The first run can take substantial time and disk space because the model files are not necessarily present before you select YuE2.
- Check the model layout if it is not detected. YuE2 files must be in the checkpoint layout expected by the installed WanGP build. After correcting the location, restart WanGP so it rescans the model directory.
- Prepare your inputs. Put musical identity in the style field and song words in the lyrics field. Use the section tags and examples in the next section before changing advanced settings.
Do not delete the original installation or checkpoint directory while troubleshooting. A missing file and an incompatible runtime can produce similar “model unavailable” messages, and preserving the initial layout makes it easier to distinguish those causes.
How should I write the style prompt and lyrics?
Write the style prompt as a compact musical brief and write the lyrics as clearly marked sections. The style field should state the genre, instruments, vocal character, language and tempo; the lyrics field should contain the words and their arrangement in the order you want sung.
Build the style prompt from five ingredients
- Genre: name the broad identity first, such as cinematic synth-pop, folk rock or jazz ballad.
- Instrumentation: specify the parts that define the arrangement, for example pulsing bass, analog pads, acoustic guitar or electronic drums.
- Vocal character: describe the lead voice in usable terms such as intimate female lead, restrained baritone or layered choir.
- Language: state the language you expect the vocal performance to use.
- Tempo: give a BPM target when the rhythmic feel matters.
A useful starting prompt is:
English, cinematic synth-pop, 112 BPM, intimate female lead vocal, pulsing bass, analog pads, crisp electronic drums, wide chorus, polished modern mix.This is intentionally specific without becoming a list of contradictory adjectives. Start with one coherent identity. If the first render is close but lacks a defining element, add one change at a time so you can tell which instruction affected the arrangement.
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Use section tags to give the song a form
Place section labels on their own lines and keep the lyric order musical. A typical structure looks like this:
[Verse]
City lights are fading slow
Footsteps echo down the road
[Pre-Chorus]
Every signal starts to glow
Pulling me where I should go
[Chorus]
We are brighter than the night
Turning sparks into a light
Hold the moment, let it run
We are rising with the sun
[Verse]
...
[Bridge]
...
[Chorus]
...[Verse], [Chorus] and [Bridge] are the clearest labels for a first pass; [Pre-Chorus] can separate a build from the refrain. Keep the text in the language named in the style prompt, avoid ambiguous section boundaries, and use a lyric length that leaves room for instrumental transitions. A concise, internally consistent request is easier to diagnose than a long prompt containing mutually exclusive genres, tempos and vocal directions.
Which YuE2 planning mode should I choose?
The cot setting determines how much symbolic planning YuE2 performs before audio synthesis. Use full planning for a new song, melody planning when a cover must follow a supplied tune, and off when you intentionally want direct generation without a symbolic plan.
| Setting | What it does | Best use | Important consequence |
|---|---|---|---|
cot="full" |
Plans melody and chords and can save an editable score. | Default for an original song where you want a structured composition and later control. | The symbolic plan becomes an inspectable artifact that can be edited and rendered again. |
cot="melody" |
Plans the melody while allowing freer accompaniment. | Covers and other cases where the vocal tune should track a source melody. | The melody plan and lyric alignment matter more than a fully predetermined chord plan. |
cot="off" |
Skips symbolic planning and generates directly. | Experiments where you prefer direct generation and do not need a saved composition plan. | You give up the score-based control surface for that render. |
| ABC input | Supplies an existing score in supported planning modes. | When you already have a melody or chord representation you want YuE2 to follow. | Validate the notation before generation; an incorrect score produces a systematically incorrect musical result. |
If you are unsure, begin with cot="full". It gives you both a listenable render and a plan you can inspect. Choose cot="off" only when the lack of an editable symbolic plan is an intentional trade-off, not because the score was overlooked.
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Once YuE2 is installed, the basic interface flow is short: choose the model, enter a style and lyrics, select a planning mode, generate, and inspect both the audio and saved metadata.
- Select YuE2 in the audio workspace. Wait until the model status shows that the required checkpoint is available.
- Enter the style prompt. Include genre, instruments, vocal character, language and BPM. Avoid adding unrelated production instructions until you have a stable baseline.
- Paste sectioned lyrics. Use clear tags and check that every intended verse, chorus and bridge appears in the right order.
- Choose the planning mode. Use
cot="full"for a new composition,cot="melody"for a cover-oriented melody workflow, orcot="off"for direct generation. If the interface exposes ABC input, attach it only when you have a score to guide the composition. - Set the output location. Use a fresh directory for each materially changed prompt, score or configuration. This prevents a new render from overwriting the evidence needed to compare it with an earlier one.
- Start generation and wait for all stages. Do not close WanGP when the audio preview appears if the application is still writing the score, plan or metadata.
- Listen through the whole file. Check the vocal entrance, section transitions, final chorus and ending rather than judging the first few seconds.
- Inspect the artifact directory. Confirm that the expected files and any truncation indicators were written before deciding whether the song is complete.
Keep the model, VAE, runtime, sampling settings and seed information shown by the application with the output. Those details are essential when you want to explain why two renders differ or reproduce a version after changing only the lyrics.
What is the staged YuE2 API workflow?
Advanced users can separate planning, semantic generation, synthesis and decoding instead of treating the process as one opaque call. The documented sequence is plan() → generate_semantic() → synthesize() → decode().
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plan()creates the symbolic composition information when the selected mode calls for planning. With full planning, this is where the melody-and-chord structure is established.generate_semantic()produces the semantic representation used to drive the musical result.synthesize()converts that representation into acoustic information.decode()turns the acoustic representation into the listenable audio file.
The separation is useful for experiments because you can identify whether a problem began in the score, semantic generation, acoustic synthesis or final decoding. The normal WanGP interface may manage these stages for you, but the artifact directory still records the intermediate products when the workflow is configured to save them.
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Yes. With a planning mode that creates a score, edit the saved score and render it again. The score is the control surface for melody and chords; changing it creates a new complete recording rather than modifying the original waveform in place.
Keep the original artifact directory untouched, copy the score into a new output directory, make one deliberate musical change, and render again. This gives you an auditable before-and-after comparison. The new render may have different acoustic details even when the score change is small, so preserve the seed and effective configuration whenever the interface exposes them.
ABC input provides another way to control a composition. Supply an existing ABC score in a planning mode that accepts it, then verify the notation and listen for the intended meter, pitches and phrase boundaries. A score controls the musical plan; it does not guarantee that the vocal timbre, mix or accompaniment will remain identical to another render.
How do I use YuE2-3B for a cover?
A cover workflow starts with a melody score transcribed from the source recording, then uses cot="melody" so YuE2 follows that tune while generating a target style and accompaniment. The official resources identify SheetSage2 as the audio-to-score transcription model used for this workflow.
- Obtain the source audio and permissions needed for your intended use. Possessing a recording does not automatically grant publication or monetization rights.
- Transcribe the melody. Use SheetSage2 or another supported transcription route to create a score, then check the notes and rhythm against the recording by ear.
- Align lyrics to sections. Mark verses, choruses and bridges so the words enter where the source melody expects them.
- Choose melody planning. Set
cot="melody"and provide the target genre, instrumentation, vocal character, language and tempo in the style prompt. - Render and audit the result. If the tune feels wrong, review both the transcription and lyric alignment before changing the style prompt.
Cover clearance has at least two separate questions: rights in the source recording and rights in the lyrics or underlying composition. A model-generated performance does not automatically clear either one, so review those rights independently before publishing.
Which files should I save for reproducible results?
Save the complete artifact directory, not just the playable audio. The generation guide describes a directory that can contain the rendered file, composition plan, semantic tokens, acoustic latents, effective configuration, timings, model identities and integrity records.
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| Artifact | Why it matters |
|---|---|
audio.flac |
The lossless listening output produced by the render. |
score.abc (when applicable) |
The editable melody-and-chord representation created by a planning workflow. |
plan.json |
The symbolic composition plan used to organize the musical result. |
| Semantic tokens | The intermediate representation generated before acoustic synthesis. |
| Acoustic latents | Intermediate acoustic data that helps explain or reproduce the synthesis stage. |
| Effective configuration | The settings actually applied, rather than only the values you intended to enter. |
| Timings | Stage timing information useful when diagnosing a stalled or unusually slow run. |
| Model identities | Names or identifiers for the model and VAE used for the render. |
| Integrity records | Checks that help establish whether a saved artifact changed after generation. |
Use a new output directory whenever you change the prompt, lyrics, score or significant settings. Inspect truncation flags in the saved result: a file can play normally and still have stopped at a token limit before the intended final section. A playable file is therefore not, by itself, proof that the requested song form was completed.
Which decoder should I use for listening and benchmarks?
Use YuE2-Vae as the default listening decoder documented for ordinary generation. YuE2-Vae-legacy is documented for reproducing the benchmark protocol, so keep benchmark-style outputs separate from everyday listening renders.
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Changing the decoder affects how the saved representation is rendered to audio; it does not replace the lyric prompt or composition plan. When comparing decoders, hold the model, plan, tokens, latents and configuration constant, write each result to a separate directory, and label which decoder produced each file.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why is WanGP not seeing YuE2?
The most common cause is a checkpoint layout or path that does not match what the installed WanGP build expects. Confirm that every YuE2 file is in the documented YuE2 directory, then restart the application so it rescans the model folders.
- Model absent from the selector: verify the checkpoint files and directory structure, restart WanGP, and check that you selected the audio workspace.
- Download or first-launch failure: restore internet access, confirm free disk space, and retry the checkpoint download. Partial files may need to be removed according to the installation guide before a clean download.
- Python, CUDA, Triton or kernel error: follow WanGP’s GPU-generation instructions for the installed card instead of combining arbitrary package versions.
- Out-of-memory error: confirm that the card meets the documented BF16 baseline, close other GPU workloads, and review WanGP’s quantization and memory-saving options. An optimization can change practical memory use, but it does not change the upstream support statement.
- Song ends early: inspect truncation flags and the saved token or timing metadata. If the output hit a token limit, shorten or restructure the lyrics before judging the model’s musical quality.
- Cover melody is inaccurate: listen back against the source, correct the transcribed score and section alignment, then regenerate with melody planning.
- Two supposedly identical renders differ: compare model identities, VAE, runtime, sampling settings and seed information from the artifact directories before changing the prompt.
What does YuE2’s licensing mean for publishing a song?
The YuE project separates software and model licensing. Its current repository states that the code, agent skill and documentation are under Apache 2.0, while the model weights are separately licensed under CC BY-NC 4.0. WanGP’s YuE2 checkpoint documentation says its converted weights retain CC BY-NC 4.0.
| Material | License identified in the project documentation | Decision you need to make |
|---|---|---|
| YuE code, agent skill and documentation | Apache 2.0 | Review the Apache terms for any software you redistribute or modify. |
| YuE2 model weights | CC BY-NC 4.0 | Do not assume commercial use, client work or monetized publishing is permitted. Check the current license and obtain permission if your use is commercial. |
| WanGP-converted YuE2 weights | CC BY-NC 4.0 retained | Conversion does not remove the non-commercial restriction; evaluate the checkpoint license separately from the application license. |
Licensing the model is only one part of release clearance. Your lyrics, samples, source recordings and cover compositions can carry their own rights. Before distributing a monetized song or delivering one to a client, document which model weights and source materials were used and confirm that each permission covers the planned use.
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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteWhat workflow gives the most reliable first result?
A disciplined baseline makes YuE2 easier to evaluate than a sequence of unrelated experiments. Start with one clear style prompt, sectioned lyrics and full planning, then change one variable per revision.
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- Confirm the supported GPU and runtime before troubleshooting musical quality.
- Generate a new original song with
cot="full"and a short, coherent lyric structure. - Listen through the complete file and inspect truncation indicators.
- Open the saved score and plan when the result is musically close but needs a different melody or chord movement.
- Render the edited score into a fresh directory, retaining the original for comparison.
- For covers, correct the transcription and lyric alignment before adding more style detail.
- When comparing versions, keep model, VAE, runtime, sampling and seed records with every artifact.
- Check the model-weight license and all underlying song rights before release.
This approach separates three decisions that are often confused: whether the runtime can generate, whether the composition is musically suitable, and whether the finished recording can legally be distributed.
Frequently asked questions
Will installing WanGP on a Mac guarantee that YuE2-3B will run?
No. WanGP provides a macOS installation path, but the YuE2 project documents a BF16-capable NVIDIA setup as its supported starting point. Treat a successful application installation and actual YuE2 compatibility as separate checks.
Why should I keep a score file if I only want an audio track?
The score lets you make a targeted musical revision without rewriting the lyric prompt from scratch. It also records what the model planned, which is useful when a later render sounds different and you need to identify whether the change came from the composition or the synthesis stage.
Can I publish a song made with the YuE2 weights in a monetized video?
Not automatically. The weights are identified as CC BY-NC 4.0, so monetized publishing and client delivery require a license review and, where necessary, permission beyond the default terms.
How can I tell whether two versions really used the same setup?
Compare the saved model identities, VAE, effective configuration, runtime details, sampling settings and seed information. If any of those differ, the files are not a controlled comparison even when the visible prompt is identical.
Frequently Asked Questions
Will installing WanGP on a Mac guarantee that YuE2-3B will run?
No. WanGP provides a macOS installation path, but the YuE2 project documents a BF16-capable NVIDIA setup as its supported starting point. Treat a successful application installation and actual YuE2 compatibility as separate checks.
Why should I keep a score file if I only want an audio track?
The score lets you make a targeted musical revision without rewriting the lyric prompt from scratch. It also records what the model planned, which is useful when a later render sounds different and you need to identify whether the change came from the composition or the synthesis stage.
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Can I publish a song made with the YuE2 weights in a monetized video?
Not automatically. The weights are identified as CC BY-NC 4.0, so monetized publishing and client delivery require a license review and, where necessary, permission beyond the default terms.
How can I tell whether two versions really used the same setup?
Compare the saved model identities, VAE, effective configuration, runtime details, sampling settings and seed information. If any of those differ, the files are not a controlled comparison even when the visible prompt is identical.
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