Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Turkish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use selimc/whisper-large-v3-turbo-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selimc/whisper-large-v3-turbo-turkish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="selimc/whisper-large-v3-turbo-turkish")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("selimc/whisper-large-v3-turbo-turkish") model = AutoModelForSpeechSeq2Seq.from_pretrained("selimc/whisper-large-v3-turbo-turkish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ggml for whispercpp?
#4
by whatnext - opened
Thank you for publishing your project. I wish you success in your endeavors. Could you please publish the binary file of this model converted to ggml format so I can try it in whispercpp?
Hello you can use whisper.cpp library with convert-h5-to-ggml.py script to convert it yourself check: https://github.com/ggml-org/whisper.cpp/blob/master/models/README.md#fine-tuned-models