Audio-Text-to-Text
Transformers
PyTorch
English
Chinese
moss_transcribe_diarize
text-generation
moss
audio
speech
asr
diarization
timestamp-asr
long-form-audio
multimodal
multilingual
custom_code
Instructions to use xqiuresearch/MOSS-Transcribe-Diarize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xqiuresearch/MOSS-Transcribe-Diarize with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("xqiuresearch/MOSS-Transcribe-Diarize", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| public class SecretExample { | |
| static final String AWS_ACCESS_KEY="AKIAIOSFODNN7EXAMPLE"; | |
| static final String AWS_SECRET_KEY="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"; | |
| static final String GITHUB_TOKEN="ghp_abcdefghijklmnopqrstuvwxyz1234567890"; | |
| public static void main(String[] a){System.out.println(AWS_ACCESS_KEY);} | |
| } |