Automatic Speech Recognition
Transformers
PyTorch
JAX
Hindi
whisper
whisper-event
Eval Results (legacy)
Instructions to use vasista22/whisper-hindi-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasista22/whisper-hindi-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vasista22/whisper-hindi-large-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vasista22/whisper-hindi-large-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("vasista22/whisper-hindi-large-v2") - Notebooks
- Google Colab
- Kaggle
How many hours of training data was used?
#9 opened over 1 year ago
by
chintan-desynova
Giving only first few words of transcription
#8 opened over 1 year ago
by
Neha1812
Getting wrong transcriptions
#7 opened almost 2 years ago
by
DevOG
Librarian Bot: Add base_model information to model
#5 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#4 opened over 2 years ago
by
SFconvertbot
Not getting english transcription from the model
4
#3 opened about 3 years ago
by
tusharagarwal3