Audio-Text-to-Text
Transformers
Safetensors
English
Chinese
moss_transcribe_diarize
text-generation
moss
audio
speech
asr
diarization
timestamp-asr
long-form-audio
multimodal
multilingual
custom_code
Eval Results
Instructions to use OpenMOSS-Team/MOSS-Transcribe-Diarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/MOSS-Transcribe-Diarize with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("OpenMOSS-Team/MOSS-Transcribe-Diarize", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Model_Architecture.png from OpenMOSS-Team/MOSS-Transcribe-Diarize: direct link, hf CLI and curl.
- Browser
- Download file 59.9 kB
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https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize/resolve/refs%2Fpr%2F10/Model_Architecture.png
- Command line
-
hf download hf://OpenMOSS-Team/MOSS-Transcribe-Diarize@refs/pr/10/Model_Architecture.png
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curl -L -o Model_Architecture.png https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize/resolve/refs%2Fpr%2F10/Model_Architecture.png
59.9 kB
