Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Czech
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use mikr/whisper-audio-concat-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikr/whisper-audio-concat-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mikr/whisper-audio-concat-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mikr/whisper-audio-concat-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("mikr/whisper-audio-concat-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run.log from mikr/whisper-audio-concat-test: direct link, hf CLI and curl.
- Browser
- Download file 1.92 MB
-
https://huggingface.co/mikr/whisper-audio-concat-test/resolve/main/run.log
- Command line
-
hf download hf://mikr/whisper-audio-concat-test/run.log
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curl -L -o run.log https://huggingface.co/mikr/whisper-audio-concat-test/resolve/main/run.log
1.92 MB
File too large to display, you can check the raw version instead.