Instructions to use vipul22/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vipul22/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vipul22/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vipul22/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("vipul22/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 100
Browse files- pytorch_model.bin +1 -1
- runs/May24_16-35-07_anaconda/1684946364.3656723/events.out.tfevents.1684946364.anaconda.57746.3 +3 -0
- runs/May24_16-35-07_anaconda/events.out.tfevents.1684946113.anaconda.57746.0 +2 -2
- runs/May24_16-35-07_anaconda/events.out.tfevents.1684946364.anaconda.57746.2 +3 -0
- runs/May24_16-43-33_anaconda/1684946853.5146263/events.out.tfevents.1684946853.anaconda.64132.1 +3 -0
- runs/May24_16-43-33_anaconda/events.out.tfevents.1684946853.anaconda.64132.0 +3 -0
- training_args.bin +1 -1
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