Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Lao
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use TopSlayer/whisper-small-lo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TopSlayer/whisper-small-lo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TopSlayer/whisper-small-lo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TopSlayer/whisper-small-lo") model = AutoModelForSpeechSeq2Seq.from_pretrained("TopSlayer/whisper-small-lo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TopSlayer/whisper-small-lo: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/TopSlayer/whisper-small-lo/resolve/main/training_args.bin
- Command line
-
hf download hf://TopSlayer/whisper-small-lo/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TopSlayer/whisper-small-lo/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 748d6d6ba44f2004e6acdf967514a5bdfaf83555444df4d4b405faab84f151b2
- Size of remote file:
- 5.5 kB
- SHA256:
- 04694b8d1657eb16a749350c049dd1ad6537a94c7c290b320cb7fd1ab2b6951e
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