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 training_args.bin from codefactory4791/whisper-small-hi: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/codefactory4791/whisper-small-hi/resolve/main/training_args.bin
- Command line
-
hf download hf://codefactory4791/whisper-small-hi/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codefactory4791/whisper-small-hi/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- d6d74aaa255bde102848cab9feb55d57c1a6517af16f90f7006d73bbf78d0031
- Size of remote file:
- 3.64 kB
- SHA256:
- c3add9e87ade0a6fe7ead4c9e9e8988c3b20b5127b97265742a5b77cce7039d2
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