Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_06 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_06")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_06") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_06", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mehtap/base_06: direct link, hf CLI and curl.
- Browser
- Download file 290 MB
-
https://huggingface.co/Mehtap/base_06/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mehtap/base_06/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mehtap/base_06/resolve/main/pytorch_model.bin
290 MB
- Xet hash:
- 800a8a3af69ee8b1226d915886bc96140c8b8602a698d49e21c7684166aa320c
- Size of remote file:
- 290 MB
- SHA256:
- 22eb4b232143f68b17c7a5a53ded33b266b729d85c6505e46d4ce7dbc84960eb
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