datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lfm2-tool-aware-dataset-v2
LFM2-Tool-Aware Dataset (v2)
Synthetic speech dataset for fine-tuning LFM2.5-Audio-class audio LLMs to handle both turns of a tool-augmented voice flow: acknowledge briefly on turn 1, then narrate the dispatcher's result on turn 2 after the coordinator injects it via set_context().
Used to train matbee/lfm2.5-audio-tool-aware-v2 (~97% accuracy on the eval split, including the new turn-2 narration class).
What's new in v2
The v1 dataset taught the model to ack-and-stop… See the full description on the dataset page: https://huggingface.co/datasets/matbee/lfm2-tool-aware-dataset-v2.lfm2-tool-aware-dataset-v1
LFM2-Tool-Aware Dataset (v1)
Synthetic speech dataset for fine-tuning LFM2.5-Audio-class audio LLMs to be tool-aware: read a tool list from the system prompt, acknowledge briefly when a user query matches a listed tool, refuse politely when no tool covers the query, and otherwise behave as a normal conversational model.
Used to train matbee/lfm2.5-audio-tool-aware-v1 (96.6% accuracy on the held-out eval split).
What this teaches a model
Voice-assistant systems often… See the full description on the dataset page: https://huggingface.co/datasets/matbee/lfm2-tool-aware-dataset-v1.moshi-tool-audio
Moshi Tool-Calling — Audio-Grounded Dataset
Audio-grounded data teaching Moshi / PersonaPlex to emit tool-call special
tokens in its inner monologue when it hears a request — and to stay quiet
otherwise (listening/idle frames are trained to PAD).
Each row is a code tensor codes[17, T] at 12.5 Hz:
rows
stream
content
0
text monologue
PAD while listening/idle, `<
1:9
Moshi audio
silence
9:17
user audio
the spoken question (edge-tts), Mimi-encoded
mask=1 marks… See the full description on the dataset page: https://huggingface.co/datasets/abrarfahim/moshi-tool-audio.