Audio-Text-to-Text
Transformers
Safetensors
English
Chinese
moss_transcribe_diarize
text2text-generation
moss
audio
speech
asr
diarization
timestamp-asr
long-form-audio
multimodal
multilingual
custom_code
Eval Results
Instructions to use ArchiveStudio/MOSS-Transcribe-Diarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArchiveStudio/MOSS-Transcribe-Diarize with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ArchiveStudio/MOSS-Transcribe-Diarize", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("ArchiveStudio/MOSS-Transcribe-Diarize", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from ArchiveStudio/MOSS-Transcribe-Diarize: direct link, hf CLI and curl.
- Browser
- Download file 226 Bytes
-
https://huggingface.co/ArchiveStudio/MOSS-Transcribe-Diarize/resolve/main/.gitattributes
- Command line
-
hf download hf://ArchiveStudio/MOSS-Transcribe-Diarize/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/ArchiveStudio/MOSS-Transcribe-Diarize/resolve/main/.gitattributes
226 Bytes
| *.bin filter=lfs diff=lfs merge=lfs -text | |
| *.safetensors filter=lfs diff=lfs merge=lfs -text | |
| *.pt filter=lfs diff=lfs merge=lfs -text | |
| *.pth filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |