Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_09 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_09 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_09")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_09") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_09", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mehtap/base_09: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/Mehtap/base_09/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Mehtap/base_09@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/base_09/resolve/refs%2Fpr%2F1/training_args.bin
3.63 kB
- Xet hash:
- d40601a9f7c29aa56aacc8c948cfbb7ff4ae8cd7c8a6432e95e949f21eea0a1e
- Size of remote file:
- 3.63 kB
- SHA256:
- 7e5cee950faaa8732a5c5a02f0116e831872f7b7aae7e31d5f0fad237236abaa
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