Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mehtap/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/Mehtap/whisper-tiny/resolve/main/training_args.bin
- Command line
-
hf download hf://Mehtap/whisper-tiny/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/whisper-tiny/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- a6f047a22b35de5291c9a9e1fa9edcee91975979f05e524f91e3408b40c6c58a
- Size of remote file:
- 3.63 kB
- SHA256:
- bfdc1c688f15371130c14ecf57a420acbf02311aee3f26bb9619e64faec91205
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