Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use Sangramsing/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sangramsing/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sangramsing/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sangramsing/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sangramsing/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sangramsing/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 2.2 MB
-
https://huggingface.co/Sangramsing/whisper-tiny/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sangramsing/whisper-tiny/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Sangramsing/whisper-tiny/resolve/main/tokenizer.json
2.2 MB
File too large to display, you can check the raw version instead.