Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hindi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-hi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from M2LabOrg/whisper-small-hi: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/M2LabOrg/whisper-small-hi/resolve/main/training_args.bin
- Command line
-
hf download hf://M2LabOrg/whisper-small-hi/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/M2LabOrg/whisper-small-hi/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- e1c13625d8a512a6f98d6dffdae5fc79073c90c52650467f9b53e4688915ed55
- Size of remote file:
- 5.24 kB
- SHA256:
- 12294cdd3ef41d38d1bcbd3d3465f957aaa5eab03bccccee5dc1118111a2349c
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