Instructions to use hiwden00/train-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiwden00/train-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hiwden00/train-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hiwden00/train-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("hiwden00/train-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hiwden00/train-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/hiwden00/train-tiny-en/resolve/main/training_args.bin
- Command line
-
hf download hf://hiwden00/train-tiny-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hiwden00/train-tiny-en/resolve/main/training_args.bin
4.35 kB
- Xet hash:
- 390974b17ec230441d711edc24dbb2a4010fa99f0e698f49894766b77e815189
- Size of remote file:
- 4.35 kB
- SHA256:
- f8dd70dcfb1971b5c34c4c15fb644b1142fde644018edebc2e24caa571b9cbc4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.