glossKit-ASR/wav2vec2-large-xlsr-53-hac

Model Description

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 for automatic speech recognition in HAC.

Model Performance

Training Details

• Base Model: facebook/wav2vec2-large-xlsr-53
• Language: HAC (hac)
• Fine-tuning Framework: PyTorch / HuggingFace Transformers

Usage

from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import torch

processor = Wav2Vec2Processor.from_pretrained("glossKit-ASR/wav2vec2-large-xlsr-53-hac")
model = Wav2Vec2ForCTC.from_pretrained("glossKit-ASR/wav2vec2-large-xlsr-53-hac")

# Process audio and transcribe
inputs = processor(audio, sampling_rate=16_000, return_tensors="pt")
with torch.no_grad():
    logits = model(**inputs).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.decode(predicted_ids[0])

Citation

If you use this model in your research, please cite:

@misc{glosskit-asr-hac,
  title={GlossKit ASR Model for HAC},
  author={GlossKit},
  year={2026},
  url={https://huggingface.co/glossKit-ASR/wav2vec2-large-xlsr-53-hac}
}

License

MIT License