Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Swedish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use SamuelHarner/whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamuelHarner/whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SamuelHarner/whisper")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SamuelHarner/whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("SamuelHarner/whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SamuelHarner/whisper: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/SamuelHarner/whisper/resolve/main/training_args.bin
- Command line
-
hf download hf://SamuelHarner/whisper/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SamuelHarner/whisper/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- eafe5136f1f18acfd9d145cfb0ac15eb183a49c0925da3e987b0b2296ec2f3a6
- Size of remote file:
- 4.79 kB
- SHA256:
- f6e8867fd0739de5a0561a1b3def34a896e0bcc57ddabbbc63eacd0a8375ef36
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