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:
# 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
Feedback: Japanese transcription feedback for future improvements
👍❤️ 1
#22 opened 7 days ago
by
ShahzaibAli4076
Training-data provenance: could you enumerate the training corpora?
#20 opened 18 days ago
by
hudsonmolthan
Title: Inconsistent transcription of quiet and louder speech
3
#19 opened 18 days ago
by
88hoon
How does it compare to Whisper + Pyannote ?
1
#18 opened 20 days ago
by
AlioLeuchtmann
reseponse_format in OpenAI-compatible vLLM Server
6
#17 opened 23 days ago
by
sebfelix
Field report: benchmarked on real French meetings vs human reference — shipped as a backend (+ one failure mode you may want to know about)
🔥 3
1
#15 opened 28 days ago
by
martossien
new
#14 opened 28 days ago
by
ANAS12345Nouri
Is the model multilingual?
8
#13 opened about 1 month ago
by
mllearner123