LFM2.5-Audio-ONNX

LFM2.5-Audio-1.5B-ONNX

ONNX export of LFM2.5-Audio-1.5B for cross-platform inference.

LFM2.5-Audio is a multimodal model supporting three modes:

• ASR (Automatic Speech Recognition): Audio → Text
• TTS (Text-to-Speech): Text → Audio
• Interleaved: Mixed text and audio input/output

Recommended Variants

• WebGPU: Use Q4 decoder + Q4 vocoder (Q8 not supported)
• Server: Q4 for efficiency, FP16 for quality

Model Files

onnx/
├── decoder.onnx                    # LFM2 backbone (FP32)
├── decoder.onnx_data*
├── decoder_fp16.onnx               # LFM2 backbone (FP16)
├── decoder_fp16.onnx_data*
├── decoder_q4.onnx                 # LFM2 backbone (Q4, recommended)
├── decoder_q4.onnx_data
├── audio_encoder.onnx              # Conformer encoder for ASR (FP32)
├── audio_encoder.onnx_data
├── audio_encoder_fp16.onnx         # Conformer encoder (FP16)
├── audio_encoder_fp16.onnx_data
├── audio_encoder_q4.onnx           # Conformer encoder (Q4)
├── audio_encoder_q4.onnx_data
├── audio_embedding.onnx            # Audio code embeddings (FP32)
├── audio_embedding_fp16.onnx       # Audio code embeddings (FP16)
├── audio_embedding_q4.onnx         # Audio code embeddings (Q4)
├── audio_detokenizer.onnx          # Neural vocoder STFT (FP32)
├── audio_detokenizer.onnx_data
├── audio_detokenizer_fp16.onnx     # Neural vocoder (FP16)
├── audio_detokenizer_fp16.onnx_data
├── audio_detokenizer_q4.onnx       # Neural vocoder (Q4)
├── audio_detokenizer_q4.onnx_data
├── vocoder_depthformer.onnx        # Audio codebook prediction (FP32)
├── vocoder_depthformer.onnx_data
├── vocoder_depthformer_fp16.onnx   # Audio codebook prediction (FP16)
├── vocoder_depthformer_fp16.onnx_data
├── vocoder_depthformer_q4.onnx     # Audio codebook prediction (Q4)
├── vocoder_depthformer_q4.onnx_data
├── embed_tokens.bin                # Text embeddings (binary)
├── embed_tokens.json               # Text embeddings metadata
├── audio_embedding.bin             # Audio embeddings (binary, for direct lookup)
├── audio_embedding.json            # Audio embeddings metadata
└── mel_config.json                 # Mel spectrogram configuration

* Large models (>2GB) split weights across multiple files:
  decoder.onnx_data, decoder.onnx_data_1, decoder.onnx_data_2, etc.
  All data files must be in the same directory as the .onnx file.

Python

Use the onnx-export repository for inference.

Installation

git clone https://github.com/Liquid4All/onnx-export.git
cd onnx-export
uv sync

ASR (Speech Recognition)

Transcribe audio to text:

uv run lfm2-audio-infer /path/to/LFM2.5-Audio-1.5B-ONNX \
    --mode asr \
    --audio input.wav \
    --precision q4

TTS (Text-to-Speech)

Generate audio from text:

uv run lfm2-audio-infer /path/to/LFM2.5-Audio-1.5B-ONNX \
    --mode tts \
    --prompt "Hello, this is a test of text to speech synthesis." \
    --output output.wav \
    --precision q4

Options:

• --system "Perform TTS. Use the UK female voice." - Custom system prompt
• --audio-temperature 0.8 - Audio sampling temperature
• --audio-top-k 64 - Top-k sampling for audio

Interleaved (Mixed Audio/Text)

Generate interleaved text and audio response from audio input:

uv run lfm2-audio-infer /path/to/LFM2.5-Audio-1.5B-ONNX \
    --mode interleaved \
    --audio input.wav \
    --output output.wav \
    --precision q4

Or from text prompt:

uv run lfm2-audio-infer /path/to/LFM2.5-Audio-1.5B-ONNX \
    --mode interleaved \
    --prompt "Respond with audio" \
    --output output.wav \
    --precision q4

CLI Options

uv run lfm2-audio-infer --help

WebGPU (Browser)

Installation

npm install onnxruntime-web @huggingface/transformers

Enable WebGPU

WebGPU is required for browser inference. To enable:

1. Chrome/Edge: Navigate to chrome://flags/#enable-unsafe-webgpu, enable, and restart
2. Verify: Check chrome://gpu for "WebGPU" status
3. Test: Run navigator.gpu.requestAdapter() in DevTools console

Inference

import * as ort from "onnxruntime-web/webgpu";
import { AutoTokenizer } from "@huggingface/transformers";

// Check WebGPU availability
if (!navigator.gpu) {
  throw new Error("WebGPU not available. Enable at chrome://flags/#enable-unsafe-webgpu");
}

ort.env.wasm.numThreads = 1;

const modelId = "LiquidAI/LFM2.5-Audio-1.5B-ONNX";
const modelBase = `https://huggingface.co/${modelId}/resolve/main`;

// Load tokenizer
const tokenizer = await AutoTokenizer.from_pretrained(modelId);

// Load ONNX sessions
async function loadSession(name, dataFiles = 1) {
  const onnxPath = `${modelBase}/onnx/${name}.onnx`;
  const externalData = [];
  for (let i = 0; i < dataFiles; i++) {
    const suffix = i === 0 ? "" : `_${i}`;
    const fileName = `${name}.onnx_data${suffix}`;