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 training_args.bin from Mehtap/base_03: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/Mehtap/base_03/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Mehtap/base_03@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/base_03/resolve/refs%2Fpr%2F1/training_args.bin
3.63 kB
- Xet hash:
- f520793bc209fe6864381f91c8314ec024a6be141558e1a75a868a99123dbfc5
- Size of remote file:
- 3.63 kB
- SHA256:
- 5e2addd78726e6e49d2bca8a66aacae257e66822654bad03e6799fafa8617141
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