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
Preserve bold styling for playground link
Browse files
README.md
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@@ -145,7 +145,7 @@ We evaluate MOSS-Transcribe-Diarize using three objective metrics: Character Err
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<td><u>6.36</u></td><td><u>12.76</u></td><td>6.40</td>
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<td><b>13.78</b></td><td><b>14.02</b></td><td><b>0.24</b></td>
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<td><b>18.22</b></td><td><b>13.94</b></td><td><b>-4.27</b></td>
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<td><b>4.46</b></td><td><b>6.97</b></td><td><u>2.51</u></td>
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<td><u>6.36</u></td><td><u>12.76</u></td><td>6.40</td>
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</tr>
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<td style="white-space: nowrap;"><a href="https://platform.mosi.cn/app/playground"><b>MOSS Transcribe Diarize Pro</b></a></td>
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<td><b>13.78</b></td><td><b>14.02</b></td><td><b>0.24</b></td>
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| 150 |
<td><b>18.22</b></td><td><b>13.94</b></td><td><b>-4.27</b></td>
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| 151 |
<td><b>4.46</b></td><td><b>6.97</b></td><td><u>2.51</u></td>
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