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RodrigoLimaRFL
/
distil-large-dev

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use RodrigoLimaRFL/distil-large-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use RodrigoLimaRFL/distil-large-dev with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="RodrigoLimaRFL/distil-large-dev")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("RodrigoLimaRFL/distil-large-dev")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("RodrigoLimaRFL/distil-large-dev", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
distil-large-dev / checkpoint-2000-epoch-33
8.34 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
RodrigoLimaRFL's picture
RodrigoLimaRFL
Saving train state of step 2000
3320fba verified about 2 years ago
  • model.safetensors
    3.03 GB
    xet
    Saving train state of step 2000 about 2 years ago
  • model_1.safetensors
    4.36 GB
    xet
    Saving train state of step 2000 about 2 years ago
  • optimizer.bin
    951 MB
    xet
    Saving train state of step 2000 about 2 years ago
  • random_states_0.pkl
    14.3 kB
    xet
    Saving train state of step 2000 about 2 years ago
  • scaler.pt
    988 Bytes
    xet
    Saving train state of step 2000 about 2 years ago
  • scheduler.bin
    1.06 kB
    xet
    Saving train state of step 2000 about 2 years ago