Any-to-Any
Transformers
Safetensors
lfm3_audio
automatic-speech-recognition
liquid
lfm3
audio
speech
edge
conversational
multilingual
custom_code
Instructions to use LiquidAI/LFM3-Audio-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiquidAI/LFM3-Audio-2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMultimodalLM model = AutoModelForMultimodalLM.from_pretrained("LiquidAI/LFM3-Audio-2B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 773 Bytes
9d49701 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"audio_out_token": "<|audio_out|>",
"audio_token": "<|audio|>",
"feature_extractor": {
"encoder_stride": 8,
"feature_extractor_type": "Lfm3AudioFeatureExtractor",
"feature_size": 128,
"hop_length": 160,
"log_floor": -12.0,
"n_fft": 400,
"normalization_divisor": 4.0,
"normalization_offset": 4.0,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400,
"auto_map": {
"AutoFeatureExtractor": "feature_extraction_lfm3_audio.Lfm3AudioFeatureExtractor"
}
},
"processor_class": "Lfm3AudioProcessor",
"auto_map": {
"AutoProcessor": "processing_lfm3_audio.Lfm3AudioProcessor"
},
"audio_tokenizer_subfolder": "audio_tokenizer"
}
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