Automatic Speech Recognition
Transformers
Safetensors
phi4_multimodal
any-to-any
nlp
code
audio
speech-summarization
speech-translation
phi-4-multimodal
phi
phi-4-mini
custom_code
Instructions to use JacobLinCool/phi-4-audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JacobLinCool/phi-4-audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JacobLinCool/phi-4-audio", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JacobLinCool/phi-4-audio", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("JacobLinCool/phi-4-audio", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "audio_compression_rate": 8, | |
| "audio_downsample_rate": 1, | |
| "audio_feat_stride": 1, | |
| "auto_map": { | |
| "AutoFeatureExtractor": "feature_extraction_phi4_multimodal.Phi4MultimodalFeatureExtractor", | |
| "AutoImageProcessor": "image_processing_phi4_multimodal_fast.Phi4MultimodalImageProcessorFast", | |
| "AutoProcessor": "processing_phi4_multimodal.Phi4MultimodalProcessor" | |
| }, | |
| "feature_extractor_type": "Phi4MultimodalFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "n_fft": 512, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "preemphasis": 0.97, | |
| "processor_class": "Phi4MultimodalProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "win_length": 400 | |
| } | |