Automatic Speech Recognition
Transformers
asr
speaker-diarization
timestamps
quantization
low-bit
arm
on-device
Instructions to use yongyizang/TinyMOSS-Diarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yongyizang/TinyMOSS-Diarize with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yongyizang/TinyMOSS-Diarize")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yongyizang/TinyMOSS-Diarize", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0910de9402be40377f48438d762069c4d78b2cfb3b53a6e59816f7b9b8ca5e3d
- Size of remote file:
- 331 MB
- SHA256:
- 6ae0e26d8bb0c77e43734782e206ad191233a29aae81d4d845d7a8aad518edd3
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