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Whisper Medium Myst Gclora

Whisper-medium adapted to the MyST dataset with GC-LoRA (Gated Convolutional LoRA), from the paper "GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation" (Interspeech 2026).

TipoOtherVersiónRevision 6c0ba83Publicador@balaji1312Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
2,85 GB
Versión
vRevision 6c0ba83
Actualizado
22 oct 2026
Publicador
@balaji1312
Descargas
3
Fuente
Hugging Face

Descripción de la fuente

Whisper-medium MyST (GC-LoRA)

Whisper-medium adapted to the MyST dataset with GC-LoRA (Gated Convolutional LoRA), from the paper "GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation" (Interspeech 2026).

  • Base model: openai/whisper-medium.en
  • Method: GC-LoRA adapter on the encoder attention output projections (rank 8, kernel 31, scaling 16)
  • MyST test WER: 8.6%
  • Code: https://github.com/balaji1312/gc_lora

Usage

The checkpoint bundles the frozen Whisper backbone together with the trained GC-LoRA adapter. Loading requires the custom modeling code in the gc_lora repository; see src/bin/decode_asr.py there for loading and decoding.

Citation

@inproceedings{shankar2026gclora,
  author    = {Shankar, Natarajan Balaji and Wang, Zilai and Zhang, Kaiyuan and Shi, Mohan and Alwan, Abeer},
  title     = {{GC-LoRA}: Gated Convolutional {LoRA} for Parameter-Efficient Acoustic Adaptation},
  booktitle = {Interspeech 2026},
  year      = {2026},
}

Fuentes

1 fuente
Hugging FacePrincipalVersión 6c0ba83c9c04e6ffd36fa7ed1c367c29f24fcbee
huggingface.co/balaji1312/whisper-medium-myst-gclora/tree/6c0ba83c9c04e6ffd36fa7ed1c367c29f24fcbee

Verificado 22 oct

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 2,85 GB · SHA-256 aceed5428f6f…6f94 · Hugging Face

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Extractos de fuentes

3 extractos

--- license: apache-2.0 language: en library_name: transformers pipeline_tag: automatic-speech-recognition tags: - whisper - automatic-speech-recognition - peft - lora - gc-lora - myst --- # Whisper-medium MyST (GC-LoRA) Whisper-medium adapted to the **MyST** dataset with **GC-LoRA** (Gated Convolutional LoRA), from the paper *"GC-LoRA: Gated Convolutional LoRA for Parameter-Efficient Acoustic Adaptation"* (Interspeech 2026). - **Base model:** `openai/whisper-medium.en` - **Method:** GC-LoRA adapter on the encoder attention output projections (rank 8, kernel 31, scaling 16) - **MyST test WER:** **8.6%** - **Code:** https://github.com/balaji1312/gc_lora ## Usage The checkpoint bundles the frozen Whisper backbone together with the trained GC-LoRA adapter. Loading requires the custom modeling code in the [gc_lora repository](https://github.com/balaji1312/gc_lora); see `src/bin/decode_asr.py` there for loading and decoding. ## Citation ```bibtex @inproceedings{shankar2026gclora, author = {Shankar, Natarajan Balaji and Wang, Zilai and Zhang, Kaiyuan and Shi, Mohan and Alwan, Abeer}, title = {{GC-LoRA}: Gated Convolutional {LoRA} for Parameter-Efficient Acoustic Adaptation}, booktitle = {Interspeech 2026}, year = {2026}, } ```

Source context: 3 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo balaji1312/whisper-medium-myst-gclora

Source context: 4 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo balaji1312/whisper-medium-myst-gclora