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)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-4-multimodal-instruct", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Decoding strategy of the Phi4 Multimodal
#50
by Zhengyang - opened
Dear authors,
thank you for the great work. What is the decoding strategy of the phi4 multimodal? Is it beam search or topk sampling? I didn't find it in the configuration file.
Best,
Zhengyang
Hi @Zhengyang ,
For speech/audio tasks, we simply used greedy search (top-1) for the benchmark. You can try other options for more diverse output if you like.
Thanks,
Ruchao