mozilla-foundation/common_voice_17_0
Updated • 5.54k • 16
How to use Da4ThEdge/base-bn-cp10k with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Da4ThEdge/base-bn-cp10k") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Da4ThEdge/base-bn-cp10k")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Da4ThEdge/base-bn-cp10k")This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset.
It is the merged model from this fine-tuned PEFT LoRA adapter: Da4ThEdge/base-bn-lora-adapter-cp10k
After 10k steps it achieves the following results on the test set:
Refer to the 20k full-trained adapter repository for more details on the finetuning: banglabridge/base-bn-lora-adapter
Base model
openai/whisper-base