Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_10")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_10") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mehtap/base_10: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/Mehtap/base_10/resolve/main/training_args.bin
- Command line
-
hf download hf://Mehtap/base_10/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/base_10/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- 0928bb860947a5a02898b3e39f7a24924807ea3dec64c1761e9d595e93d6b057
- Size of remote file:
- 3.63 kB
- SHA256:
- 7ef3f3b1869232266615ed48d91e46d4ee32d3b17758473d0d9377e8041f6dda
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