Automatic Speech Recognition
Transformers
Safetensors
Korean
phi4mm
text-generation
custom_code
Eval Results (legacy)
Instructions to use junnei/Phi-4-multimodal-instruct-ko-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junnei/Phi-4-multimodal-instruct-ko-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="junnei/Phi-4-multimodal-instruct-ko-speech", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("junnei/Phi-4-multimodal-instruct-ko-speech", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6185c47ef9dbefe57a2bc040f30a1fe769eed49e4a1a5c7cd98c051d1ade7997
- Size of remote file:
- 5.37 kB
- SHA256:
- 75ef167e66bdb9f4adc3dc5cdf3375b802fc9aabc61b18af3b6e51766e810f51
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