Instructions to use BuzzASR/sindhi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BuzzASR/sindhi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BuzzASR/sindhi")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BuzzASR/sindhi") model = AutoModelForSpeechSeq2Seq.from_pretrained("BuzzASR/sindhi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from BuzzASR/sindhi: direct link, hf CLI and curl.
- Browser
- Download file 3.09 GB
-
https://huggingface.co/BuzzASR/sindhi/resolve/main/model.safetensors
- Command line
-
hf download hf://BuzzASR/sindhi/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/BuzzASR/sindhi/resolve/main/model.safetensors
3.09 GB
- Xet hash:
- 84e047c26500ca383609f74d973b2645161b84b0d60123b985fc15b4ec1ad282
- Size of remote file:
- 3.09 GB
- SHA256:
- 0e3e298e79f1496ab1d64fb82b336986068e824930eec4d17cb99ee688b92e14
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