Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Urdu
whisper
Speech
ASR
Whisper-fine-tuning
Instructions to use shaeel12/whisper-tiny-urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shaeel12/whisper-tiny-urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shaeel12/whisper-tiny-urdu", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shaeel12/whisper-tiny-urdu") model = AutoModelForSpeechSeq2Seq.from_pretrained("shaeel12/whisper-tiny-urdu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- ur
metrics:
- wer
base_model:
- openai/whisper-tiny
pipeline_tag: automatic-speech-recognition
library_name: transformers
tags:
- Speech
- ASR
- Whisper-fine-tuning
datasets:
- ai4bharat/Kathbath
- google/fleurs
This model was fine-tuned on a combination of the following speech corpuses:
- ai4bharat/Kathbath (via Hugging Face)
- google/fleurs (via Hugging Face)
- Mozilla Common Voice (Urdu Subset): Sourced directly from the official Mozilla Data Collective.