Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_02")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_02") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mehtap/base_02: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/Mehtap/base_02/resolve/main/training_args.bin
- Command line
-
hf download hf://Mehtap/base_02/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mehtap/base_02/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- 762779f1e263dd8a731b5e79c2b11418112a813a2db0e3cc4c18a9177bc888b2
- Size of remote file:
- 3.63 kB
- SHA256:
- 81fe339a1713a02969e0d8e48d757797a026b63174b0f03f35582c5f2b9ce52f
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