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simpletuner /minimax-music3:9740bd64

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
train_data
string
ZIP or tar of matching .wav/.mp3/.flac, .txt style captions, and .lyrics files
regularisation_data
string
Optional audio/.txt/.lyrics archive for frozen-base prior preservation
trigger_word
string
Optional instance prompt replacing per-track captions
max_train_steps
integer
750

Min: 1

Max: 50000

Optimizer updates
checkpoint_interval
integer
250

Min: 1

Max: 5000

Save every N updates
lora_rank
integer
64

Min: 1

Max: 256

LoRA rank
lora_dropout
number
0

Max: 0.5

LoRA dropout
learning_rate
number
0.00008

Min: 0.0000001

Max: 0.001

Learning rate
window_mode
None
continuation
Continuation supervises the end of a context window; prefix and random supervise the entire selected window
continuation_crop_mode
None
full
Full keeps the song opening; random may start later while retaining causal context
caption_dropout
number
0

Max: 1

Probability of omitting style captions while retaining lyrics
max_audio_duration
number
30

Min: 5.12

Max: 300

Maximum visible training window in seconds
enable_regional_compile
boolean
True
Compile repeated transformer blocks
attention_mechanism
None
kohaku-fa-auto
Attention backend
gradient_checkpointing
boolean
True
Recompute language-model activations to reduce memory use
dataloader_prefetch
boolean
True
Prepare upcoming training batches in the background
seed
integer
42
Training seed
hub_model_id
string
Optional Hugging Face repository for the trained adapter
hf_token
string
Write-capable Hugging Face token for uploading the adapter
push_checkpoints_to_hub
boolean
True
Upload intermediate checkpoints to the Hub in the background

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}