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
Download preprocessor_config.json from microsoft/Phi-4-multimodal-instruct: direct link, hf CLI and curl.
- Browser
- Download file 483 Bytes
-
https://huggingface.co/microsoft/Phi-4-multimodal-instruct/resolve/refs%2Fpr%2F55/preprocessor_config.json
- Command line
-
hf download hf://microsoft/Phi-4-multimodal-instruct@refs/pr/55/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/microsoft/Phi-4-multimodal-instruct/resolve/refs%2Fpr%2F55/preprocessor_config.json
483 Bytes
| { | |
| "audio_compression_rate": 8, | |
| "audio_downsample_rate": 1, | |
| "audio_feat_stride": 1, | |
| "dynamic_hd": 36, | |
| "feature_extractor_type": "Phi4MultimodalFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "image_processor_type": "Phi4MMImageProcessor", | |
| "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 | |
| } | |