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LiquidAI/LFM2.5-Audio-1.5B-GGUF

sourceHugging Faceotherupdated 6mo agoView on Hugging Face
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Model Card

<div align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" alt="Liquid AI" style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;" /> <div style="display: flex; justify-content: center; gap: 0.5em;"> <a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> • <a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> • <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> • <a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a> </div> </div>

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LFM2.5-Audio-1.5B

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-Audio-1.5B

Runners

runners folder contains runners for various architectures including

  • llama-liquid-audio-cli
  • llama-liquid-audio-server

🏃 How to run LFM2.5

CLI

Set env variables.

export CKPT=/path/to/LFM2.5-Audio-1.5B-GGUF
export INPUT_WAV=/path/to/input.wav
export OUTPUT_WAV=/path/to/output.wav

ASR (audio -> text)

bash
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform ASR." --audio $INPUT_WAV

TTS (text -> audio)

bash
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform TTS." -p "Hi, how are you?" --output $OUTPUT_WAV

Interleaved (audio/text -> audio + text)

bash
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Respond with interleaved text and audio." --audio $INPUT_WAV --output $OUTPUT_WAV

Server

Start server

export CKPT=/path/to/LFM2.5-Audio-1.5B-GGUF
./llama-liquid-audio-server -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf

Use liquid_audio_chat.py script to communicate with the server.

bash
uv run liquid_audio_chat.py

Source Code for Runners

Runners are built from https://github.com/ggml-org/llama.cpp/pull/18641. It's WIP and will take time to land in upstream.

Demo

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