Instructions to use switlydev/whisper-small-tr-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use switlydev/whisper-small-tr-custom with PEFT:
Task type is invalid.
- Transformers
How to use switlydev/whisper-small-tr-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="switlydev/whisper-small-tr-custom")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("switlydev/whisper-small-tr-custom") model = AutoModelForSpeechSeq2Seq.from_pretrained("switlydev/whisper-small-tr-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from switlydev/whisper-small-tr-custom: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
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https://huggingface.co/switlydev/whisper-small-tr-custom/resolve/main/tokenizer.json
- Command line
-
hf download hf://switlydev/whisper-small-tr-custom/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/switlydev/whisper-small-tr-custom/resolve/main/tokenizer.json
3.93 MB
File too large to display, you can check the raw version instead.