Instructions to use TheAIchemist13/whisper-hindi-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheAIchemist13/whisper-hindi-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheAIchemist13/whisper-hindi-base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheAIchemist13/whisper-hindi-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheAIchemist13/whisper-hindi-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TheAIchemist13/whisper-hindi-base: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/TheAIchemist13/whisper-hindi-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TheAIchemist13/whisper-hindi-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TheAIchemist13/whisper-hindi-base/resolve/main/pytorch_model.bin
290 MB
- Xet hash:
- 75cb383b95d0c733fda9c0714250328e7258c5ab91ed5372963e131f09f1dc41
- Size of remote file:
- 290 MB
- SHA256:
- fe4ff5751aff5fbbe59582eb7ff0da1e5f0598d38b9c673b4c2033d0acd6308e
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