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 pytorch_model.bin from Mehtap/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/Mehtap/whisper-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mehtap/whisper-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mehtap/whisper-tiny/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- 1387fbef01b41f2eef1e07047dbfb06adbd430d9e42b322c0019ee781cb0ba6c
- Size of remote file:
- 151 MB
- SHA256:
- aca8c8898384d2af7df01e5b6898bc38264c85533535231f131b5aa7ff74d093
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