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vitthalbhandari/
mms-1b-all-aft-one-meh

Name: mms-1b-all-aft-one-meh
Availability: InStock

safetensors

wav2vec2

audio

automatic-speech-recognition

mms

adapter

meh

mozilla-foundation/common_voice_spontaneous_speech

cc-by-nc-4.0

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MMS Adapter Fine-tuned for Southwestern Tlaxiaco Mixtec

This model is a fine-tuned version of facebook/mms-1b-all on the Mozilla Common Voice Spontaneous Speech dataset for Southwestern Tlaxiaco Mixtec (meh).

Training

Base model: facebook/mms-1b-all
Fine-tuning method: Adapter layers
Dataset: Mozilla Common Voice Spontaneous Speech

Usage

python

from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import torch

processor = Wav2Vec2Processor.from_pretrained("vitthalbhandari/mms-1b-all-aft-one-meh")
model = Wav2Vec2ForCTC.from_pretrained("vitthalbhandari/mms-1b-all-aft-one-meh")

# Load adapter
model.load_adapter("meh")

# Transcribe audio
inputs = processor(audio_array, sampling_rate=16000, return_tensors="pt")
with torch.no_grad():
    logits = model(**inputs).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids)