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LFM JP
LFM JP is Liquid AI's Hugging Face collection for Japanese-tuned LFM models, grouping a newer LFM2.5-1.2B-JP text model with LFM2.5-Audio-1.5B-JP for Japanese speech and text workflows.
The official collection links native model cards and GGUF variants. The text model card covers Japanese-English assistant use, tool calling, structured outputs, and local inference paths, while the audio model card covers speech-to-speech conversation, ASR, TTS, and the liquid-audio package. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
Japanese-tuned LFM collection
The LFM JP collection brings together Liquid AI models aimed at Japanese text and speech work, including the 1.2B JP text checkpoint, a GGUF export, and the 1.5B JP audio model with its own GGUF variant.
Why it stands out
Text agents and voice in one lane
The useful angle is the pairing. One card points toward Japanese-English assistants, tool calls, and structured outputs; the other points toward Japanese audio input, generated speech, ASR, TTS, and conversational speech-to-speech use.
Availability
Model cards, formats, and examples
The Hugging Face pages include model files, model details, GGUF variants, chat and tool-use examples for the text model, plus liquid-audio setup and speech examples for the audio model.
Why it matters
Why readers may notice it
This is a good one to watch because Japanese local AI is not only a text-model problem. A useful assistant stack also needs speech input, speech output, tool behavior, and formats that people can actually run or compare.
What readers may want to know
Where it fits
LFM JP fits most naturally in the speech and audio model layer, with a clear overlap into local assistant and agent workflows. It is most relevant to readers comparing Japanese voice assistants, bilingual helper models, and smaller on-device model paths.
Reporting note
What the two model cards clarify
The text card is the cleaner place to inspect tool use, structured outputs, context length, and local inference frameworks. The audio card is the cleaner place to inspect Japanese speech-to-speech interaction, ASR, TTS, audio generation modes, and liquid-audio setup.
Before using
What readers may want to review
Which model and format fits the job: text checkpoint, audio checkpoint, GGUF export, or another related LFM2.5 variant.
Runtime requirements and setup details for Transformers, vLLM, llama.cpp, MLX, LM Studio, or liquid-audio before planning a workflow.
How Japanese audio, private speech data, voice likeness, and provider or local-runtime data handling should be treated before testing real conversations.
The model-card notes on intended use and limits, especially where the text model is framed more around assistants and tool workflows than knowledge-heavy tasks.
Reader fit
Who may find it relevant
Readers tracking Japanese speech models, ASR, TTS, and speech-to-speech interaction.
Builders comparing Japanese-English assistants, tool-use behavior, structured outputs, or local model formats.
Less relevant for readers who only want a hosted general chatbot with no setup work.
Editorial note
Why it is included here
LFM JP gives readers one official place to inspect Liquid AI's Japanese text and speech direction, from tool-using local assistants to voice interaction and audio model experiments.
Source links
Official materials
Reader note
Before relying on this entry
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Fish Audio S2 Pro
fishaudio/s2-pro
A text-to-speech model with detailed control over prosody and emotional delivery.
VoxCPM2
openbmb/VoxCPM2
A multilingual text-to-speech model with voice design, controllable voice cloning, and streaming support.
Cohere Transcribe
CohereLabs/cohere-transcribe-03-2026
A 2B parameter automatic speech recognition model for audio-in, text-out transcription across 14 languages.
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