Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_05")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_05") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mehtap/base_05: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/Mehtap/base_05/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Mehtap/base_05@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mehtap/base_05/resolve/refs%2Fpr%2F1/pytorch_model.bin
290 MB
- Xet hash:
- 6f08a5f78c57679ba129d92cff9863645755cb356c1bcec793e2f81922259617
- Size of remote file:
- 290 MB
- SHA256:
- 8c4a76baf549d1c5bc921853e28132102a4d0fd2417e06cb50f3ba1cf15ef1db
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