omniASR-W2V-300M

56
—
by
aadel4
Embedding Model
OTHER
New
56 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Code Examples

Usagepythontransformers
from transformers import Wav2Vec2Model, Wav2Vec2FeatureExtractor
import torch, torchaudio

extractor = Wav2Vec2FeatureExtractor.from_pretrained("aadel4/omniASR-W2V-300M")
model     = Wav2Vec2Model.from_pretrained("aadel4/omniASR-W2V-300M")
model.eval()

waveform, sr = torchaudio.load("audio.wav")
if sr != 16_000:
    waveform = torchaudio.functional.resample(waveform, sr, 16_000)

inputs = extractor(
    waveform.squeeze().numpy(), sampling_rate=16_000,
    return_tensors="pt", padding=True
)
with torch.no_grad():
    embeddings = model(**inputs).last_hidden_state  # (1, T, 1024)

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