Whisper Large V3 Turbo - Nepali to English Translation
Fine-tuned Whisper Large V3 Turbo model for Nepali audio → English text translation using LoRA adapters.
Model Details
- Base Model: openai/whisper-large-v3-turbo
- Task: Translation (Nepali → English)
- Source Language: Nepali (audio)
- Target Language: English (text)
- Training Data: 776 samples
Usage
from transformers import WhisperForConditionalGeneration, WhisperProcessor, pipeline
from peft import PeftModel
# Load base model
base_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v3-turbo")
# Load LoRA adapters
model = PeftModel.from_pretrained(base_model, "Anryul/whisper-nepali-lora")
processor = WhisperProcessor.from_pretrained("Anryul/whisper-nepali-lora")
# Create translation pipeline
pipe = pipeline(
"automatic-speech-recognition",
model=model,
tokenizer=processor.tokenizer,
feature_extractor=processor.feature_extractor,
)
# Translate Nepali audio to English
result = pipe("nepali_audio.wav", generate_kwargs={"task": "translate", "language": "nepali"})
print(result["text"]) # English translation
Training
- Epochs: 10
- Task: Translation
- Batch Size: 8
- Learning Rate: 1e-3
- LoRA Rank: 32
Citation
If you use this model, please cite the original Whisper paper and dataset.