Automatic Speech Recognition
Transformers
Safetensors
phi4mm
text-generation
nlp
code
audio
speech-summarization
speech-translation
visual-question-answering
phi-4-multimodal
phi
phi-4-mini
custom_code
Eval Results
Instructions to use microsoft/Phi-4-multimodal-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/Phi-4-multimodal-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="microsoft/Phi-4-multimodal-instruct", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-4-multimodal-instruct", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 705 Bytes
d93d2f6 698b586 d93d2f6 698b586 d93d2f6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"auto_map": {
"AutoProcessor": "processing_phi4_multimodal.Phi4MultimodalProcessor",
"AutoImageProcessor": "image_processing_phi4_multimodal_fast.Phi4MultimodalImageProcessorFast",
"AutoFeatureExtractor": "feature_extraction_phi4_multimodal.Phi4MultimodalFeatureExtractor"
},
"audio_compression_rate": 8,
"audio_downsample_rate": 1,
"audio_feat_stride": 1,
"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
}
|