Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Maithili
whisper
maithili
fine-tuned
speech
audio
indian-languages
devanagari
Eval Results (legacy)
Instructions to use rockerritesh/whisper-tiny-maithili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rockerritesh/whisper-tiny-maithili with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rockerritesh/whisper-tiny-maithili")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rockerritesh/whisper-tiny-maithili") model = AutoModelForSpeechSeq2Seq.from_pretrained("rockerritesh/whisper-tiny-maithili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rockerritesh/whisper-tiny-maithili: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
-
https://huggingface.co/rockerritesh/whisper-tiny-maithili/resolve/main/tokenizer.json
- Command line
-
hf download hf://rockerritesh/whisper-tiny-maithili/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/rockerritesh/whisper-tiny-maithili/resolve/main/tokenizer.json
3.93 MB
File too large to display, you can check the raw version instead.