Instructions to use ICTNLP/StreamUni-Phi4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use ICTNLP/StreamUni-Phi4 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("ICTNLP/StreamUni-Phi4", set_active=True) - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- ICTNLP/StreamUni
base_model:
- microsoft/Phi-4-multimodal-instruct
pipeline_tag: audio-text-to-text
library_name: adapter-transformers
The model for the paper 'StreamUni: Achieving Streaming Speech Translation with a Unified Large Speech-Language Model'
Usage
Please refer to Github Page
Requirements
Phi-4 family has been integrated in the 4.48.2 version of transformers. The current transformers version can be verified with: pip list | grep transformers.
We suggest to run with Python 3.10.
Examples of required packages:
flash_attn==2.7.4.post1
torch==2.6.0
transformers==4.48.2
accelerate==1.3.0
soundfile==0.13.1
pillow==11.1.0
scipy==1.15.2
torchvision==0.21.0
backoff==2.2.1
peft==0.13.2