Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/whisper-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/whisper-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/whisper-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/whisper-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/whisper-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mehtap/whisper-base: direct link, hf CLI and curl.
- Browser
- Download file 3.57 kB
-
https://huggingface.co/Mehtap/whisper-base/resolve/main/training_args.bin
- Command line
-
hf download hf://Mehtap/whisper-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/whisper-base/resolve/main/training_args.bin
3.57 kB
- Xet hash:
- dc67beda66caf5529dd3db463c89f0af2a6ae21d37c805b1ff5985e3847227f6
- Size of remote file:
- 3.57 kB
- SHA256:
- d8ac63f1184d85af40c8195c37220c9b54337c10601350ff15c2f89e590325a9
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