Automatic Speech Recognition
Transformers
PyTorch
Galician
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use zuazo/whisper-large-v2-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zuazo/whisper-large-v2-gl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zuazo/whisper-large-v2-gl")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("zuazo/whisper-large-v2-gl") model = AutoModelForSpeechSeq2Seq.from_pretrained("zuazo/whisper-large-v2-gl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zuazo/whisper-large-v2-gl: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/zuazo/whisper-large-v2-gl/resolve/main/training_args.bin
- Command line
-
hf download hf://zuazo/whisper-large-v2-gl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zuazo/whisper-large-v2-gl/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- c12e32d1414b2124a088978fb10c9d3f47f44f403487f6486503b9b8b415ff39
- Size of remote file:
- 4.16 kB
- SHA256:
- e51897d054e8a9a07a68c777f3bd165e096e2d10e21a1df01c9002449593831f
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