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 tokenizer.json from AXERA-TECH/MOSS-Transcribe-Diarize-0.9B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/resolve/main/tokenizer.json
- Command line
-
hf download hf://AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AXERA-TECH/MOSS-Transcribe-Diarize-0.9B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 2e66cc2841d06bfaca1dada8c35fc4e0cc78340822aad69f0ff82e699890145f
- Size of remote file:
- 11.4 MB
- SHA256:
- bcf03774334462d6e34b5005cb11120a62275f146ee2953e68731ecdbce84fbb
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