Instructions to use codefactory4791/whisper-small-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codefactory4791/whisper-small-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="codefactory4791/whisper-small-hi")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("codefactory4791/whisper-small-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("codefactory4791/whisper-small-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from codefactory4791/whisper-small-hi: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/codefactory4791/whisper-small-hi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://codefactory4791/whisper-small-hi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codefactory4791/whisper-small-hi/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 56a7c477b74a7d48c78a7bd412cf68a62ab94a39ea6981dd6d83690c941422cd
- Size of remote file:
- 967 MB
- SHA256:
- 5df1293e855d59e8e22e8852709d4c37881e28a3e22e10b05f76117be62a4501
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