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 pytorch_model.bin from Mehtap/whisper-base: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/Mehtap/whisper-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mehtap/whisper-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mehtap/whisper-base/resolve/main/pytorch_model.bin
290 MB
- Xet hash:
- c36dabee6e4a003343b5f106b6a993f51347641bffd0920ac5127a71f676d155
- Size of remote file:
- 290 MB
- SHA256:
- aa6b88af3894b4ef4aad17d70540cc617a57024a6fb9f1a34902b9d4913840f4
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