elbruno/personaplex-7b-v1-onnx
By elbruno · ↓ 0 · ♥ 1 · Updated 2026-02-27
What's in this repo
This page lists the files in elbruno/personaplex-7b-v1-onnx, including lm_backbone.onnx, mimi_decoder.onnx, mimi_encoder.onnx.
- 3 ONNX models (.onnx files)
- 6 files, including 3 .onnx, 1 .md, 1 .data
- Last updated 2026-02-27
ONNX files
| File | Size | Download |
|---|---|---|
| lm_backbone.onnx | — | Download |
| mimi_decoder.onnx | — | Download |
| mimi_encoder.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
PersonaPlex-7B-v1 ONNX
ONNX-exported components of NVIDIA PersonaPlex-7B-v1 for use with ElBruno.PersonaPlex C# library.
Files
| File | Size | Description |
|---|---|---|
| mimi_encoder.onnx | 178 MB | Mimi audio encoder (24kHz audio -> discrete tokens) |
| mimi_decoder.onnx | 170 MB | Mimi audio decoder (discrete tokens -> 24kHz audio) |
Architecture
These are the Mimi audio codec components of PersonaPlex, based on the Moshi architecture:
-
Encoder: SEANet convolutional encoder + ProjectedTransformer + SplitResidualVectorQuantizer
- Input: [batch, 1, samples] float32 (24kHz mono audio)
- Output: [batch, 8, frames] int64 (8 codebooks, ~12.5 frames/sec)
-
Decoder: SplitResidualVectorQuantizer + ProjectedTransformer + SEANet convolutional decoder
- Input: [batch, 8, frames] int64
- Output: [batch, 1, samples] float32
Usage with C#
`csharp using ElBruno.PersonaPlex.Pipeline;
// Models download automatically on first run using var pipeline = await PersonaPlexPipeline.CreateAsync(); `
Export Details
- Exported from PyTorch using orch.onnx.export (opset 17)
- Source: nvidia/personaplex-7b-v1
- Mimi model: 79.3M parameters
- Dynamic axes enabled for batch size and sequence length
License
MIT (same as the export tooling). The base model weights are under NVIDIA Open Model License.
Model info
Created: 2026-02-27
Updated: 2026-02-27
View on Hugging FaceFiles (6)
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