Instructions to use AXERA-TECH/MOSS-Transcribe-Diarize-0.9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/MOSS-Transcribe-Diarize-0.9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AXERA-TECH/MOSS-Transcribe-Diarize-0.9B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/MOSS-Transcribe-Diarize-0.9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.embed_tokens.weight.npy from AXERA-TECH/MOSS-Transcribe-Diarize-0.9B: direct link, hf CLI and curl.
- Browser
- Download file 622 MB
-
https://huggingface.co/AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/resolve/main/model.embed_tokens.weight.npy
- Command line
-
hf download hf://AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/model.embed_tokens.weight.npy
-
curl -L -o model.embed_tokens.weight.npy https://huggingface.co/AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/resolve/main/model.embed_tokens.weight.npy
622 MB
- Xet hash:
- b1438dc774dfdfa8927339262e68a32aa8b5eef6f952a763174d69dde1841416
- Size of remote file:
- 622 MB
- SHA256:
- b7d5373ccd262a46c6fb5bfb765aac7d13548b801f9835587f5d464638066995
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