Instructions to use tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3/resolve/main/training_args.bin
- Command line
-
hf download hf://tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/tolgaaktas/distilled_whisper-small_teacher_whisper-large-v3/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- a063d31d4d5ffd56ff084dc275ca14b45944846b51fc61fa4bfe624a7b3f302c
- Size of remote file:
- 5.69 kB
- SHA256:
- d9c74f9a9be425ff5e425c0fc45bfa118822e3915038fe8593b9f6917791f1b0
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