Automatic Speech Recognition
Transformers
Safetensors
Nepali
whisper
nepali
fine-tuned
audio
asr
Eval Results (legacy)
Instructions to use devrahulbanjara/whisper-small-nepali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devrahulbanjara/whisper-small-nepali with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devrahulbanjara/whisper-small-nepali")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("devrahulbanjara/whisper-small-nepali") model = AutoModelForMultimodalLM.from_pretrained("devrahulbanjara/whisper-small-nepali") - Notebooks
- Google Colab
- Kaggle
File size: 379 Bytes
1f6a335 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<|endoftext|>",
"eos_token": "<|endoftext|>",
"is_local": true,
"language": null,
"model_max_length": 1000000000000000019884624838656,
"predict_timestamps": false,
"processor_class": "WhisperProcessor",
"task": null,
"tokenizer_class": "WhisperTokenizer",
"unk_token": "<|endoftext|>"
}
|