Expand description
Mimi neural audio tokenizer support. Mimi neural audio tokenizer support.
Mimi is the neural audio codec used by Moshi-family realtime models. This module implements backend-neutral checkpoint parameters, the split residual vector quantizer, and the non-streaming SEANet/transformer encoder and decoder used to map between PCM and Mimi codebook tokens.
Structs§
- Config
- Mimi codec configuration.
- Conv1x1
NoBias - Bias-free 1x1 convolution over
[batch, channels, frames]tensors. - Euclidean
Codebook - Euclidean codebook backed by EMA cluster statistics.
- Mimi
- Mimi audio tokenizer.
- Mimi
Parameter Requirement - Exact released-checkpoint requirement for one Mimi parameter.
- Prepared
Mimi Artifact - Header-admitted Mimi artifact with an immutable exact parameter plan.
- Residual
Vector Quantization - Residual vector quantization layers.
- Residual
Vector Quantizer - Residual vector quantizer branch.
- Selected
Mimi Artifact - Backend-admitted Mimi plan ready for native materialization.
- Split
Residual Vector Quantizer - Split residual vector quantizer used by Mimi.
- Vector
Quantization - Single vector-quantization layer.
Enums§
- Mimi
Artifact Error - Failure while preparing a released Mimi artifact from neutral metadata.
- Mimi
Construction Error - Failure while selecting, materializing, or constructing Mimi on a backend.
- Resample
Method - Mimi resampling strategy.
Functions§
- construct
- Selects generic backend mechanisms, then constructs Mimi through the exact neutral artifact plan.
- prepare_
checkpoint - Inspects and admits an exact released Mimi SafeTensors artifact without reading tensor payloads.
- prepare_
source - Admits an already opened backend-neutral SafeTensors-compatible source. No tensor payload is acquired during preparation.
- released_
checkpoint_ requirements - Returns the complete released-checkpoint schema derived from Mimi’s authoritative parameter topology without inspecting an artifact.