Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_03 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_03")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_03") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mehtap/base_03: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/Mehtap/base_03/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mehtap/base_03/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mehtap/base_03/resolve/main/pytorch_model.bin
290 MB
- Xet hash:
- 212c1f6cb91932e08e291b192f1d4b84db34eae22d2b3df50adeb24b189e573b
- Size of remote file:
- 290 MB
- SHA256:
- ec125065eb5eb4af4b571f2b7363c6cadc72f0afb8932e026771e52c84414c1a
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