Instructions to use OmarEXP/XLSR-2B-FT-DVOICE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OmarEXP/XLSR-2B-FT-DVOICE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="OmarEXP/XLSR-2B-FT-DVOICE")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("OmarEXP/XLSR-2B-FT-DVOICE") model = AutoModelForCTC.from_pretrained("OmarEXP/XLSR-2B-FT-DVOICE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from OmarEXP/XLSR-2B-FT-DVOICE: direct link, hf CLI and curl.
- Browser
- Download file 8.64 GB
-
https://huggingface.co/OmarEXP/XLSR-2B-FT-DVOICE/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://OmarEXP/XLSR-2B-FT-DVOICE/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/OmarEXP/XLSR-2B-FT-DVOICE/resolve/main/pytorch_model.bin
8.64 GB
- Xet hash:
- 6167bbf4d9f5029724298a281c0aac9a8acb62d1e2ac8da2b60899502fd4096b
- Size of remote file:
- 8.64 GB
- SHA256:
- 452b97bddaa6bc1974dc7bd87f6aef5150576e27f662fd479884a7b7f731b8e1
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